Feedback signals from image data of athletic performance

ABSTRACT

Aspects of this disclosure relate to improving an athlete&#39;s ability to synchronize the movement of their body in time. Certain embodiments provide a feedback system that allows an athlete (or another individual, such as a trainer) to comprehend and optimize the timing of one or more components or features of an athletic movement. Image data, such as video, of an athlete performing physical activity may be utilized (alone or in combination with non-image data) may be used to generate and emit real-time feedback signals to provide an indication of tempo to the athlete. Still further aspects relate to using image and/or other sensor data to detect improper timing and/or movements of an athlete, and in response generating real-time feedback signals.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application Ser.No. 61/793,472, entitled “Feedback Signals from Image Data of AthleticPerformance,” filed Mar. 15, 2013, which application is incorporated byreference herein.

BACKGROUND

Athletes, both amateur and professional, often desire to improve theirperformance for a particular sport or athletic activity. In addition toimproving physical prowess, athletes may see large sport-specificimprovements with drills directed towards vision, reaction time, orother abilities. Improper use of equipment or devices may actually lowerathletic performance. Similarly, incorrectly administering drills orroutines can also prevent the athlete to be properly trained and/or leadto a false conclusion that an athlete is not performing to thresholdlevel.

Many athletes and trainers, therefore, are often unable to accuratelydetermine athletic attributes and performance levels of the athlete.This causes difficulty in training the athlete as well as accuratelycomparing the athlete's performance to others. Existing options includerequiring the athlete to travel to a specific location (often hundredsof miles away) to a specific facility on a specific date to conduct aseries of drills that will permit a more accurate determination of theirabilities and performance level. Unfortunately, the athlete may not beable to afford the trip and/or be available on the specific date.Additionally, the athlete may have a sub-par performance on one day andthus be considered well-below their actual performance level. This oftenleads to athletes not attending these events, and as such, continue tomisjudge their performance of specific activities and drills. Therefore,despite heavy training, the athlete may not be improving in the properareas in an efficient manner.

Therefore, in view of the foregoing, improved systems and methods aredesirable. Aspects of this disclosure are directed towards novel systemsand methods that address one or more of these deficiencies. Furtheraspects relate to minimizing other shortcomings in the art.

BRIEF SUMMARY

The following presents a simplified summary in order to provide a basicunderstanding of some aspects of the disclosure. The summary is not anextensive overview of the disclosure. It is neither intended to identifykey or critical elements of the disclosure nor to delineate the scope ofthe disclosure. The following summary merely presents some concepts ofthe disclosure in a simplified form as a prelude to the descriptionbelow.

Aspects of this disclosure relate to system and methods configured toimprove the athlete's ability to synchronize the movement of their bodyin time. Certain embodiments provide a feedback system that allows anathlete (or another individual, such as a trainer) to comprehend andoptimize the timing of one or more components or features of an athleticmovement. Certain aspects relate to providing feedback to an athleteregarding the athlete's performance of a physical activity. The feedbackmay be provided in real-time such that the athlete may obtain feedbackduring performance of the athletic activity. In accordance with oneembodiment, image data of the athlete performing the athletic activity,or at least a portion thereof, may be obtained. In one embodiment, aplurality of sequential images during an athlete's performance of aphysical activity may be obtained. The image data may be processed inreal-time to identify the athlete performing a first feature of a firstathletic movement. For example, the physical activity of swinging a golfclub may have several movements, such as a backswing movement and aforward swing movement. Within each movement, several features may beidentified.

One or more features of a movement may be detected from a motionparameter. For example, if the athletic movement is a backswing of agolf swing, then a feature of that backswing may be based on at leastone of a velocity value, an acceleration value, a location of a bodyportion of the athlete, or a location of a sporting device within theimage data. In certain embodiments, a determination of the motionparameter may be determined based upon, at least in part, that avelocity value or an acceleration value meets a first threshold. Incertain embodiments, the motion parameter may be used to generate oralter the generated feedback signal. For example, an audible feedbacksignal may be modulated based upon the speed or acceleration of abaseball bat's motion.

Determining whether a feature has occurred may include determiningwhether one or more movements of objects represented by image data meeta threshold criterion. Exemplary criterion may include a movementcriterion and a movement quality criterion. In one embodiment, a firstcriterion may serve as a filter that identifies certain images that maybe of interest and the second criterion may further identifies what datawithin this group fits a more stringent criteria. In yet anotherembodiment, the first and second criteria may be independent. A firstthreshold may detect whether a first body portion moved. The selectionand/or utilization of the one or more portions of the athlete's bodyrepresented within the image data may be based on the predeterminedphysical activity, user input, historical data, and combinations thereofamong others.

One or more image capturing devices may capture images at different orvariable frame rates. For example, an image capturing device may captureimages at a variable rate between 50 to 100 frames per second (fps).Therefore, determinations of movement (and/or movement quality) mayutilize rate of capture information to accurately determine timeintervals between frames of data that may be separated by uneven periodsof time.

In certain implementations, landmarks/distance calibrations may beutilized from time-stamped image data to allow for precise measuring ofperformance. For example, objects represented by image data may beutilized to determine whether movement thresholds are met. For example,markings on a field (such as yard lines) may be used to calibratedistance measurements. In certain embodiments, objects may be identifiedand upon identification, used in calibration processes. Such calibrationtechniques are not limited to stationary objects. In certainembodiments, the predetermined physical activity may be used (either inwhole or in part) to select which body portion(s) are utilized and/orwhether the movement of the portion(s)—as represented within thecaptured image data—meet a threshold. In certain embodiments, systemsand methods may be implemented that utilize a different body portionbased upon characteristics of the image data.

Further aspects relate to generating and transmitting a feedback signalin response to identifying the performance of the feature(s). Thetransmission may be in real-time. In certain embodiments, image data mayindicate that the athlete is performing a second or additional featuresof a first athletic movement. Additional feedback signals, such asaudible signals, may be based upon the movement properties of the secondfeature may be transmitted. In one implementation, the athlete receivesaudio feedback during performance of the athletic movement configured toprovide audible tempo feedback in regards to the athlete's performanceof the first and second features of the athletic activity. The audiofeedback signal may include a first audible tone at a first frequencyand a second audio feedback signal may be generated by modulating theaudible tone to a second frequency. In yet other embodiments, visualand/or tactile feedback signals may be utilized.

Identification of features may comprise identifying an initiation imagecomprising: identifying pixels that correspond to at least one of aspecific first body portion or sporting object, wherein the first bodyportion or sporting object is selected based upon a predeterminedphysical activity the athlete is to perform; and determining, based uponthe identified pixels, whether the pixel data is altered between aplurality of images within the sequential images such that thealteration satisfies a first threshold. Processing image data maycomprise the utilization of an optical flow process. An optical flowprocess may be provided as an input to a motion entropy determinationprocess comprising: providing flow field data comprising apixel-distance change of an identified object from a first image to asecond image; and using the flow field data to identify a specific typeof motion of the athlete represented in the image data duringperformance of the physical activity.

As one example of another embodiment, the physical activity may be agolf swing having an upswing athletic movement and a subsequentdownswing athletic movement. Detecting image data that the athlete isperforming the first feature may include detecting pixel data indicativethat a golf club is within a first distance from a ground surface anddetermining that the second athlete is performing the second feature ofthe upswing athletic movement is detected from pixel data indicativethat the golf club is within a second distance from a ground surface.

Further aspects relate to transmitting proper timing to the athletebased upon detecting a first and a second feature of the athleticmovement. For example, based upon the detection of at least one of thefirst and the second feature, a feedback signal may be transmitted at apredetermined time. It may be based upon the occurrence of the first orsecond feature and be configured to indicate the proper timing for theathlete to perform an additional feature of the athletic performance.

A performance attribute of the athlete may be determined from thethreshold information as well as other image-derived data. As oneexample, an initiation image (alone or in combination with anotherimage) may be used to determine at least one performance attribute ofthe athlete. Example attributes may include, but are not limited to:speed, reaction, endurance, and combinations thereof.

Further aspects may be utilized to calculate an athletic rating of theuser. In certain embodiments, a rating may be a sport-specific athleticrating. For example, a single athlete may have a different rating forfootball and running rating score.

These and other aspects of the embodiments are discussed in greaterdetail throughout this disclosure, including the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is illustrated by way of example and not limitedin the accompanying figures in which like reference numerals indicatesimilar elements and in which:

FIG. 1 illustrates an example of a system that may be configured toprovide personal training and/or obtain data from the physical movementsof a user in accordance with example embodiments;

FIG. 2 illustrates an example computer device that may be part of or incommunication with the system of FIG. 1.

FIG. 3 shows an illustrative sensor assembly that may be worn by a userin accordance with example embodiments;

FIG. 4 shows another example sensor assembly that may be worn by a userin accordance with example embodiments;

FIG. 5 shows illustrative locations for sensory input which may includephysical sensors located on/in a user's clothing and/or be based uponidentification of relationships between two moving body parts of theuser;

FIG. 6 is a flowchart of an example method that may be utilized todetermine athletic attributes from image data in accordance with oneexemplary embodiment;

FIG. 7 is a flowchart showing an example implementation of utilizing atriggering event in accordance with one embodiment;

FIG. 8 is a flowchart showing an example implementation of transmittinga generating and transmitting feedback signals in accordance with oneembodiment

FIGS. 9A and 9B show an example activity space comprising illustrativetest elements; and

FIG. 10 is a flowchart of an example method that may be implemented togenerate an athleticism rating using imaging data in accordance withcertain embodiments.

DETAILED DESCRIPTION

Aspects of this disclosure relate to determining athletic attributes ofan athlete from image data. One or more determinations may be basedalterations of image data between different images (or frames), such asalterations in pixels representing objects or portions of objects. Imagedata may be utilized to determine whether certain thresholds are met.Various threshold levels may be applied to one or more objectsrepresented in the image data. In certain implementations, an athlete'sperformance of a physical activity, such as for example, a sprint oragility drill, or battery of field-based tests, may be analyzedaccording to image data. In certain implementations, landmarks/distancecalibrations may be utilized from time-stamped image data to allow forprecise measuring of performance (including, but not limited to: sprintor agility times, flight time for vertical jump, distance for throws).Data retrieved or derived from the image data may be used in scoringand/or ranking athletes. Such data may be used to provide trainingadvice or regimes to the athletes or other individuals, such as coachesor trainers.

In the following description of the various embodiments, reference ismade to the accompanying drawings, which form a part hereof, and inwhich is shown by way of illustration various embodiments in which thedisclosure may be practiced. It is to be understood that otherembodiments may be utilized and structural and functional modificationsmay be made without departing from the scope and spirit of the presentdisclosure. Further, headings within this disclosure should not beconsidered as limiting aspects of the disclosure. Those skilled in theart with the benefit of this disclosure will appreciate that the exampleembodiments are not limited to the example headings.

Aspects of this disclosure involve obtaining, storing, and/or processingathletic data relating to the physical movements of an athlete. Theathletic data may be actively or passively sensed and/or stored in oneor more non-transitory storage mediums. Still further aspects relate tousing athletic data to generate an output, such as for example,calculated athletic attributes, feedback signals to provide guidance,and/or other information. These and other aspects will be discussed inthe context of the following illustrative examples of a personaltraining system.

I. Example Personal Training System

A. Illustrative Computing Devices

Aspects of this disclosure relate to systems and methods that may beutilized across a plurality of networks. In this regard, certainembodiments may be configured to adapt to dynamic network environments.Further embodiments may be operable in differing discrete networkenvironments. FIG. 1 illustrates an example of a personal trainingsystem 100 in accordance with example embodiments. Example system 100may include one or more interconnected networks, such as theillustrative body area network (BAN) 102, local area network (LAN) 104,and wide area network (WAN) 106. As shown in FIG. 1 (and describedthroughout this disclosure), on or more networks (e.g., BAN 102, LAN104, and/or WAN 106), may overlap or otherwise be inclusive of eachother. Those skilled in the art will appreciate that the illustrativenetworks 102-106 are logical networks that may each comprise one or moredifferent communication protocols and/or network architectures and yetmay be configured to have gateways to each other or other networks. Forexample, each of BAN 102, LAN 104 and/or WAN 106 may be operativelyconnected to the same physical network architecture, such as cellularnetwork architecture 108 and/or WAN architecture 110. For example,portable electronic device 112, which may be considered a component ofboth BAN 102 and LAN 104, may comprise a network adapter or networkinterface card (NIC) configured to translate data and control signalsinto and from network messages according to one or more communicationprotocols, such as the Transmission Control Protocol (TCP), the InternetProtocol (IP), and the User Datagram Protocol (UDP) through one or moreof architectures 108 and/or 110. These protocols are well known in theart, and thus will not be discussed here in more detail.

Network architectures 108 and 110 may include one or more informationdistribution network(s), of any type(s) or topology(s), alone or incombination(s), such as for example, cable, fiber, satellite, telephone,cellular, wireless, etc. and as such, may be variously configured suchas having one or more wired or wireless communication channels(including but not limited to: WiFi®, Bluetooth®, Near-FieldCommunication (NFC) and/or ANT technologies). Thus, any device within anetwork of FIG. 1, (such as portable electronic device 112 or any otherdevice described herein) may be considered inclusive to one or more ofthe different logical networks 102-106. With the foregoing in mind,example components of an illustrative BAN and LAN (which may be coupledto WAN 106) will be described.

1. Example Local Area Network

LAN 104 may include one or more electronic devices, such as for example,computer device 114. Computer device 114, or any other component ofsystem 100, may comprise a mobile terminal, such as a telephone, musicplayer, tablet, netbook or any portable device. In other embodiments,computer device 114 may comprise a media player or recorder, desktopcomputer, server(s), a gaming console, such as for example, a Microsoft®XBOX, Sony® PlayStation, and/or a Nintendo® Wii gaming consoles. Thoseskilled in the art will appreciate that these are merely example devicesfor descriptive purposes and this disclosure is not limited to anyconsole or computing device.

Those skilled in the art will appreciate that the design and structureof computer device 114 may vary depending on several factors, such asits intended purpose. One example implementation of computer device 114is provided in FIG. 2, which illustrates a block diagram of computingdevice 200. Those skilled in the art will appreciate that the disclosureof FIG. 2 may be applicable to any device disclosed herein. Device 200may include one or more processors, such as processor 202-1 and 202-2(generally referred to herein as “processors 202” or “processor 202”).Processors 202 may communicate with each other or other components viaan interconnection network or bus 204. Processor 202 may include one ormore processing cores, such as cores 206-1 and 206-2 (referred to hereinas “cores 206” or more generally as “core 206”), which may beimplemented on a single integrated circuit (IC) chip.

Cores 206 may comprise a shared cache 208 and/or a private cache (e.g.,caches 210-1 and 210-2, respectively). One or more caches 208/210 maylocally cache data stored in a system memory, such as memory 212, forfaster access by components of the processor 202. Memory 212 may be incommunication with the processors 202 via a chipset 216. Cache 208 maybe part of system memory 212 in certain embodiments. Memory 212 mayinclude, but is not limited to, random access memory (RAM), read onlymemory (ROM), and include one or more of solid-state memory, optical ormagnetic storage, and/or any other medium that can be used to storeelectronic information. Yet other embodiments may omit system memory212.

System 200 may include one or more I/O devices (e.g., I/O devices 214-1through 214-3, each generally referred to as I/O device 214). I/O datafrom one or more I/O devices 214 may be stored at one or more caches208, 210 and/or system memory 212. Each of I/O devices 214 may bepermanently or temporarily configured to be in operative communicationwith a component of system 100 using any physical or wirelesscommunication protocol.

Returning to FIG. 1, four example I/O devices (shown as elements116-122) are shown as being in communication with computer device 114.Those skilled in the art will appreciate that one or more of devices116-122 may be stand-alone devices or may be associated with anotherdevice besides computer device 114. For example, one or more I/O devicesmay be associated with or interact with a component of BAN 102 and/orWAN 106. I/O devices 116-122 may include, but are not limited toathletic data acquisition units, such as for example, sensors. One ormore I/O devices may be configured to sense, detect, and/or measure anathletic parameter from a user, such as user 124. Examples include, butare not limited to: an accelerometer, a gyroscope, alocation-determining device (e.g., GPS), light (including non-visiblelight) sensor, temperature sensor (including ambient temperature and/orbody temperature), sleep pattern sensors, heart rate monitor,image-capturing sensor, moisture sensor, force sensor, compass, angularrate sensor, and/or combinations thereof among others.

In further embodiments, I/O devices 116-122 may be used to provide anoutput (e.g., audible, visual, or tactile cue) and/or receive an input,such as a user input from athlete 124. Example uses for theseillustrative I/O devices are provided below, however, those skilled inthe art will appreciate that such discussions are merely descriptive ofsome of the many options within the scope of this disclosure. Further,reference to any data acquisition unit, I/O device, or sensor is to beinterpreted disclosing an embodiment that may have one or more I/Odevice, data acquisition unit, and/or sensor disclosed herein or knownin the art (either individually or in combination).

Information from one or more devices (across one or more networks) maybe used (or be utilized in the formation of) a variety of differentparameters, metrics or physiological characteristics including but notlimited to: motion parameters, such as speed, acceleration, distance,steps taken, direction, relative movement of certain body portions orobjects to others, or other motion parameters which may be expressed asangular rates, rectilinear rates or combinations thereof, physiologicalparameters, such as calories, heart rate, sweat detection, effort,oxygen consumed, oxygen kinetics, and other metrics which may fallwithin one or more categories, such as: pressure, impact forces,information regarding the athlete, such as height, weight, age,demographic information and combinations thereof.

System 100 may be configured to transmit and/or receive athletic data,including the parameters, metrics, or physiological characteristicscollected within system 100 or otherwise provided to system 100. As oneexample, WAN 106 may comprise sever 111. Server 111 may have one or morecomponents of system 200 of FIG. 2. In one embodiment, server 111comprises at least a processor and a memory, such as processor 206 andmemory 212. Server 111 may be configured to store computer-executableinstructions on a non-transitory computer-readable medium. Theinstructions may comprise athletic data, such as raw or processed datacollected within system 100. System 100 may be configured to transmitdata, such as energy expenditure points, to a social networking websiteor host such a site. Server 111 may be utilized to permit one or moreusers to access and/or compare athletic data. As such, server 111 may beconfigured to transmit and/or receive notifications based upon athleticdata or other information.

Returning to LAN 104, computer device 114 is shown in operativecommunication with a display device 116, an image-capturing device 118,sensor 120 and exercise device 122, which are discussed in turn belowwith reference to example embodiments. In one embodiment, display device116 may provide audio-visual cues to athlete 124 to perform a specificathletic movement. The audio-visual cues may be provided in response tocomputer-executable instruction executed on computer device 114 or anyother device, including a device of BAN 102 and/or WAN. Display device116 may be a touchscreen device or otherwise configured to receive auser-input.

In one embodiment, data may be obtained from image-capturing device 118and/or other sensors, such as sensor 120, which may be used to detect(and/or measure) athletic parameters, either alone or in combinationwith other devices, or stored information. Image-capturing device 118and/or sensor 120 may comprise a transceiver device. In one embodimentsensor 128 may comprise an infrared (IR), electromagnetic (EM) oracoustic transceiver. For example, image-capturing device 118, and/orsensor 120 may transmit waveforms into the environment, includingtowards the direction of athlete 124 and receive a “reflection” orotherwise detect alterations of those released waveforms. Those skilledin the art will readily appreciate that signals corresponding to amultitude of different data spectrums may be utilized in accordance withvarious embodiments. In this regard, devices 118 and/or 120 may detectwaveforms emitted from external sources (e.g., not system 100). Forexample, devices 118 and/or 120 may detect heat being emitted from user124 and/or the surrounding environment. Thus, image-capturing device 126and/or sensor 128 may comprise one or more thermal imaging devices. Inone embodiment, image-capturing device 126 and/or sensor 128 maycomprise an IR device configured to perform range phenomenology.

In one embodiment, exercise device 122 may be any device configurable topermit or facilitate the athlete 124 performing a physical movement,such as for example a treadmill, step machine, etc. There is norequirement that the device be stationary. In this regard, wirelesstechnologies permit portable devices to be utilized, thus a bicycle orother mobile exercising device may be utilized in accordance withcertain embodiments. Those skilled in the art will appreciate thatequipment 122 may be or comprise an interface for receiving anelectronic device containing athletic data performed remotely fromcomputer device 114. For example, a user may use a sporting device(described below in relation to BAN 102) and upon returning home or thelocation of equipment 122, download athletic data into element 122 orany other device of system 100. Any I/O device disclosed herein may beconfigured to receive activity data.

2. Body Area Network

BAN 102 may include two or more devices configured to receive, transmit,or otherwise facilitate the collection of athletic data (includingpassive devices). Exemplary devices may include one or more dataacquisition units, sensors, or devices known in the art or disclosedherein, including but not limited to I/O devices 116-122. Two or morecomponents of BAN 102 may communicate directly, yet in otherembodiments, communication may be conducted via a third device, whichmay be part of BAN 102, LAN 104, and/or WAN 106. One or more componentsof LAN 104 or WAN 106 may form part of BAN 102. In certainimplementations, whether a device, such as portable device 112, is partof BAN 102, LAN 104, and/or WAN 106, may depend on the athlete'sproximity to an access points permit communication with mobile cellularnetwork architecture 108 and/or WAN architecture 110. User activityand/or preference may also influence whether one or more components areutilized as part of BAN 102. Example embodiments are provided below.

User 124 may be associated with (e.g., possess, carry, wear, and/orinteract with) any number of devices, such as portable device 112,shoe-mounted device 126, wrist-worn device 128 and/or a sensinglocation, such as sensing location 130, which may comprise a physicaldevice or a location that is used to collect information. One or moredevices 112, 126, 128, and/or 130 may not be specially designed forfitness or athletic purposes. Indeed, aspects of this disclosure relateto utilizing data from a plurality of devices, some of which are notfitness devices, to collect, detect, and/or measure athletic data. Incertain embodiments, one or more devices of BAN 102 (or any othernetwork) may comprise a fitness or sporting device that is specificallydesigned for a particular sporting use. As used herein, the term“sporting device” includes any physical object that may be used orimplicated during a specific sport or fitness activity. Exemplarysporting devices may include, but are not limited to: golf balls,basketballs, baseballs, soccer balls, footballs, powerballs, hockeypucks, weights, bats, clubs, sticks, paddles, mats, and combinationsthereof. In further embodiments, exemplary fitness devices may includeobjects within a sporting environment where a specific sport occurs,including the environment itself, such as a goal net, hoop, backboard,portions of a field, such as a midline, outer boundary marker, base, andcombinations thereof.

In this regard, those skilled in the art will appreciate that one ormore sporting devices may also be part of (or form) a structure andvice-versa, a structure may comprise one or more sporting devices or beconfigured to interact with a sporting device. For example, a firststructure may comprise a basketball hoop and a backboard, which may beremovable and replaced with a goal post. In this regard, one or moresporting devices may comprise one or more sensors, such one or more ofthe sensors discussed above in relation to FIGS. 1-3, that may provideinformation utilized, either independently or in conjunction with othersensors, such as one or more sensors associated with one or morestructures. For example, a backboard may comprise a first sensorsconfigured to measure a force and a direction of the force by abasketball upon the backboard and the hoop may comprise a second sensorto detect a force. Similarly, a golf club may comprise a first sensorconfigured to detect grip attributes on the shaft and a second sensorconfigured to measure impact with a golf ball.

Looking to the illustrative portable device 112, it may be amulti-purpose electronic device, that for example, includes a telephoneor digital music player, including an IPOD®, IPAD®, or iPhone®, branddevices available from Apple, Inc. of Cupertino, Calif. or Zune® orMicrosoft® Windows devices available from Microsoft of Redmond, Wash. Asknown in the art, digital media players can serve as an output device,input device, and/or storage device for a computer. Device 112 may beconfigured as an input device for receiving raw or processed datacollected from one or more devices in BAN 102, LAN 104, or WAN 106. Inone or more embodiments, portable device 112 may comprise one or morecomponents of computer device 114. For example, portable device 112 maybe include a display 116, image-capturing device 118, and/or one or moredata acquisition devices, such as any of the I/O devices 116-122discussed above, with or without additional components, so as tocomprise a mobile terminal.

B. Illustrative Apparel/Accessory Sensors

In certain embodiments, I/O devices may be formed within or otherwiseassociated with user's 124 clothing or accessories, including a watch,armband, wristband, necklace, shirt, shoe, or the like. These devicesmay be configured to monitor athletic movements of a user. It is to beunderstood that they may detect athletic movement during user's 124interactions with computer device 102 and/or operate independently ofcomputer device 102 (or any other device disclosed herein). For example,one or more devices in BAN 102 may be configured to function as an-allday activity monitor that measures activity regardless of the user'sproximity or interactions with computer device 102. It is to be furtherunderstood that the sensory system 302 shown in FIG. 3 and the deviceassembly 400 shown in FIG. 4, each of which are described in thefollowing paragraphs, are merely illustrative examples.

i. Shoe-Mounted Device

In certain embodiments, device 126 shown in FIG. 1, may comprisefootwear which may include one or more sensors, including but notlimited to those disclosed herein and/or known in the art. FIG. 3illustrates one example embodiment of a sensor system 302 providing oneor more sensor assemblies 304. Assembly 304 may comprise one or moresensors, such as for example, an accelerometer, gyroscope,location-determining components, force sensors and/or or any othersensor disclosed herein or known in the art. In the illustratedembodiment, assembly 304 incorporates a plurality of sensors, which mayinclude force-sensitive resistor (FSR) sensors 306; however, othersensor(s) may be utilized. Port 308 may be positioned within a solestructure 309 of a shoe, and is generally configured for communicationwith one or more electronic devices. Port 308 may optionally be providedto be in communication with an electronic module 310, and the solestructure 309 may optionally include a housing 311 or other structure toreceive the module 310. The sensor system 302 may also include aplurality of leads 312 connecting the FSR sensors 306 to the port 308,to enable communication with the module 310 and/or another electronicdevice through the port 308. Module 310 may be contained within a wellor cavity in a sole structure of a shoe, and the housing 311 may bepositioned within the well or cavity. In one embodiment, at least onegyroscope and at least one accelerometer are provided within a singlehousing, such as module 310 and/or housing 311. In at least a furtherembodiment, one or more sensors are provided that, when operational, areconfigured to provide directional information and angular rate data. Theport 308 and the module 310 include complementary interfaces 314, 316for connection and communication.

In certain embodiments, at least one force-sensitive resistor 306 shownin FIG. 3 may contain first and second electrodes or electrical contacts218, 318, 320 and a force-sensitive resistive material 322 disposedbetween the electrodes 318, 320 to electrically connect the electrodes318, 320 together. When pressure is applied to the force-sensitivematerial 322, the resistivity and/or conductivity of the force-sensitivematerial 322 changes, which changes the electrical potential between theelectrodes 318, 320. The change in resistance can be detected by thesensor system 302 to detect the force applied on the sensor 316. Theforce-sensitive resistive material 322 may change its resistance underpressure in a variety of ways. For example, the force-sensitive material322 may have an internal resistance that decreases when the material iscompressed. Further embodiments may utilize “volume-based resistance”may be measured, which may be implemented through “smart materials.” Asanother example, the material 322 may change the resistance by changingthe degree of surface-to-surface contact, such as between two pieces ofthe force sensitive material 322 or between the force sensitive material322 and one or both electrodes 318, 320. In some circumstances, thistype of force-sensitive resistive behavior may be described as“contact-based resistance.”

ii. Wrist-Worn Device

As shown in FIG. 4, device 400 (which may resemble or comprise sensorydevice 128 shown in FIG. 1, may be configured to be worn by user 124,such as around a wrist, arm, ankle, neck or the like. Device 400 mayinclude an input mechanism, such as a depressible input button 402configured to be used during operation of the device 400. The inputbutton 402 may be operably connected to a controller 404 and/or anyother electronic components, such as one or more of the elementsdiscussed in relation to computer device 114 shown in FIG. 1. Controller404 may be embedded or otherwise part of housing 406. Housing 406 may beformed of one or more materials, including elastomeric components andcomprise one or more displays, such as display 408. The display may beconsidered an illuminable portion of the device 400. The display 408 mayinclude a series of individual lighting elements or light members suchas LED lights 410. The lights may be formed in an array and operablyconnected to the controller 404. Device 400 may include an indicatorsystem 412, which may also be considered a portion or component of theoverall display 408. Indicator system 412 can operate and illuminate inconjunction with the display 408 (which may have pixel member 414) orcompletely separate from the display 408. The indicator system 412 mayalso include a plurality of additional lighting elements or lightmembers, which may also take the form of LED lights in an exemplaryembodiment. In certain embodiments, indicator system may provide avisual indication of goals, such as by illuminating a portion oflighting members of indicator system 412 to represent accomplishmenttowards one or more goals. Device 400 may be configured to display dataexpressed in terms of activity points or currency earned by the userbased on the activity of the user, either through display 408 and/orindicator system 412.

A fastening mechanism 416 can be disengaged wherein the device 400 canbe positioned around a wrist or portion of the user 124 and thefastening mechanism 416 can be subsequently placed in an engagedposition. In one embodiment, fastening mechanism 416 may comprise aninterface, including but not limited to a USB port, for operativeinteraction with computer device 114 and/or devices, such as devices 120and/or 112. In certain embodiments, fastening member may comprise one ormore magnets. In one embodiment, fastening member may be devoid ofmoving parts and rely entirely on magnetic forces.

In certain embodiments, device 400 may comprise a sensor assembly (notshown in FIG. 4). The sensor assembly may comprise a plurality ofdifferent sensors, including those disclosed herein and/or known in theart. In an example embodiment, the sensor assembly may comprise orpermit operative connection to any sensor disclosed herein or known inthe art. Device 400 and or its sensor assembly may be configured toreceive data obtained from one or more external sensors.

iii. Apparel and/or Body Location Sensing

Element 130 of FIG. 1 shows an example sensory location which may beassociated with a physical apparatus, such as a sensor, data acquisitionunit, or other device. Yet in other embodiments, it may be a specificlocation of a body portion or region that is monitored, such as via animage capturing device (e.g., image capturing device 118). In certainembodiments, element 130 may comprise a sensor, such that elements 130 aand 130 b may be sensors integrated into apparel, such as athleticclothing. Such sensors may be placed at any desired location of the bodyof user 124. Sensors 130 a/b may communicate (e.g., wirelessly) with oneor more devices (including other sensors) of BAN 102, LAN 104, and/orWAN 106. In certain embodiments, passive sensing surfaces may reflectwaveforms, such as infrared light, emitted by image-capturing device 118and/or sensor 120. In one embodiment, passive sensors located on user's124 apparel may comprise generally spherical structures made of glass orother transparent or translucent surfaces which may reflect waveforms.Different classes of apparel may be utilized in which a given class ofapparel has specific sensors configured to be located proximate to aspecific portion of the user's 124 body when properly worn. For example,golf apparel may include one or more sensors positioned on the apparelin a first configuration and yet soccer apparel may include one or moresensors positioned on apparel in a second configuration.

FIG. 5 shows illustrative locations for sensory input (see, e.g.,sensory locations 130 a-130 o). In this regard, sensors may be physicalsensors located on/in a user's clothing, yet in other embodiments,sensor locations 130 a-130 o may be based upon identification ofrelationships between two moving body parts. For example, sensorlocation 130 a may be determined by identifying motions of user 124 withan image-capturing device, such as image-capturing device 118. Thus, incertain embodiments, a sensor may not physically be located at aspecific location (such as one or more of sensor locations 130 a-1306o), but is configured to sense properties of that location, such as withimage-capturing device 118 or other sensor data gathered from otherlocations. In this regard, the overall shape or portion of a user's bodymay permit identification of certain body parts. Regardless of whetheran image-capturing device is utilized and/or a physical sensor locatedon the user 124, and/or using data from other devices, (such as sensorysystem 302), device assembly 400 and/or any other device or sensordisclosed herein or known in the art is utilized, the sensors may sensea current location of a body part and/or track movement of the bodypart. In one embodiment, sensory data relating to location 130 m may beutilized in a determination of the user's center of gravity (a.k.a,center of mass). For example, relationships between location 130 a andlocation(s) 1306 f/130 l with respect to one or more of location(s) 1306m-1306 o may be utilized to determine if a user's center of gravity hasbeen elevated along the vertical axis (such as during a jump) or if auser is attempting to “fake” a jump by bending and flexing their knees.In one embodiment, sensor location 1306 n may be located at about thesternum of user 124. Likewise, sensor location 146 o may be locatedapproximate to the naval of user 124. In certain embodiments, data fromsensor locations 130 m-130 o may be utilized (alone or in combinationwith other data) to determine the center of gravity for user 124. Infurther embodiments, relationships between multiple several sensorlocations, such as sensors 130 m-130 o, may be utilized in determiningorientation of the user 124 and/or rotational forces, such as twistingof user's 124 torso. Further, one or more locations, such aslocation(s), may be utilized to as a center of moment location. Forexample, in one embodiment, one or more of location(s) 130 m-130 o mayserve as a point for a center of moment location of user 124. In anotherembodiment, one or more locations may serve as a center of moment ofspecific body parts or regions.

II. Systems and Methods for Determining Athletic Attributes from ImageData

Aspects of this disclosure relate to system and methods configured toimprove the athlete's ability to synchronize the movement of their bodyin time. Certain embodiments provide a feedback system that allows anathlete (or another individual, such as a trainer) to comprehend andoptimize the timing of one or more components or features of an athleticmovement.

Aspects of this disclosure relate to processing data taken while a userperforms an athletic activity to determine athletic attributes. Imagedata, such as video, of an athlete performing physical activity may beutilized to generate and emit real-time feedback signals to provide anindication of tempo to the athlete. Further aspects relate to usingdata, including but not limited to image data and/or any sensordisclosed herein including those discussed in reference to FIG. 1, togenerate emit real-time feedback signals alerting the athlete of propertiming of one or more features or component of an athletic movement.Still further aspects relate to using image and/or other sensor data todetect improper timing and/or movements of an athlete, and in responsegenerating real-time feedback signals. These and other aspects will bediscussed in the context of the following illustrative examples, whichare meant to provide examples, but not limit, the scope of thisdisclosure.

FIG. 6 shows flowchart600 of an example implementation that may beutilized in accordance with certain embodiments of this disclosure. Oneor more aspects of the methodologies provided as part of FIG. 6 or anyother portion of this disclosure may be utilized to determine anathletic attribute of an individual. In certain embodiments, the tempoof one or more athletic movements may be determined. In this regard, oneor more aspects of FIG. 6 may be used to provide a feedback system toallow an athlete to discern which tempo, power, speed, or other motionparameter during an athletic movement is correlated with superiorresults. Other aspects may be utilized to calculate an athletic ratingof the user. In certain embodiments, a rating may be a sport-specificathletic rating. For example, a single athlete may have a differentrating for golf and football. In further embodiments, the rating may bespecific to a position or type of activity within the sport. Forexample, a first golf rating may relate to the tempo of a club swingwhile a second rating may relate to the tempo of a putter swing. Asother examples, for a soccer rating, a first rating may be related to aforward position and a second rating may be related to a goalieposition. For an American football rating, a first rating may relate toa quarterback position and the second rating may be for a running backposition. Similarly, in the running sports, a first rating may be asprint rating while another rating is related to longer distances.

Block 602 may be initiated to receive a plurality of sequential imagesof an athlete performing a physical activity. In one embodiment, thesequential images may be received in real-time. Those skilled in the artwill appreciate that there may be inherent delays in receiving, storing,and/or processing the received data, even for “live” or real-time data.The physical activity may include any physical movement of the athlete,and be inclusive of the athlete's participation within a sport oractivity with other participants. Those skilled in the art understandthat most physical activities are not simple single movements. Instead,most activities include multiple athletic movements. As one example, agolf swing may be an athletic activity. A golf swing is known torequire, at its simplest form, at least two distinct movements from thegolfer: a backswing and a subsequent forward swing that makes contactwith the golf ball. Further, a backswing movement is often not uniformbut includes several distinct features, such as a starting point, anacceleration aspect as the club extends backwards, and the terminationpoint, in which the forward swing begins. Similarly, a basketball jumpshot comprises a plurality of movements, such as the athlete propellingoff the court, bending of the elbows and movements of the wrist. Underdifferent embodiments, each of these aspects of the jump shot may eitherbe classified as a movement or a feature or component of a specificmovement, nonetheless, it would beneficial to provide the athlete anindication of their tempo in regards to these aspects. Therefore, one ormore embodiments encompass the reception of a plurality of sequentialimages comprising image data.

The image data may have been captured from an image capturing device,including any one or more of: a portable entertainment device, astereoscopic camera, an infrared camera, a game console camera, andcombinations thereof or other device known in the art, including but notlimited to one or more of image capturing device 118, sensor, 120,computer device 114, and/or portable device 112 described in relation toFIG. 1. As discussed above, image data may be captured and/or receivedin real-time, such as to permit the athlete to obtain feedback duringthe performance of the athletic activity. In one embodiment, block 602captures a plurality images wherein at least a first image comprisesimage data of an athlete before initiating performance of apredetermined physical activity and a plurality of subsequent imagescomprise image data of the athlete performing the predetermined physicalactivity. The image data may comprise pixel data.

In one embodiment, computer device 114 and/or device 112 may comprise animage capturing device (see, e.g., image capturing device 118 and sensor120 shown in FIG. 1) and the trigger may be transmitted from at leastone of a speaker, display, or light emitting device (e.g., displaydevice 116 shown in FIG. 1 and/or display 408 of device 400 shown inFIG. 4), which may be directly connected to the device itself (such asbeing integral with the device or connected locally or via variousnetwork architecture (e.g., cellular network architecture 108 and/or WANarchitecture 110). Yet other embodiments may comprise an electronicdevice, such as device 128 or computer device 114, configured to receiveand/or decipher a trigger transmitted from a separate and distinctdevice, object or thing (including human-generated inputs, e.g., a humanvoice), such as via one or more sensing devices. In this regard, it isenvisioned that the trigger of block 604 (and other triggers disclosedherein) may be machine-sensible with respect to at least one sensoryinput of one device in accordance with many different embodiments.

One or more embodiments may trigger the capturing of image data basedupon a triggering event. Triggering events may be utilized to elicit anaction from a user, such as to instruct an athlete to perform a physicalaction, such as shooting a jump shot, swinging a golf club or any otherphysical activity. In certain embodiments, triggering events may beutilized to elicit a portion of an action, such as performing just thebackswing or the forward swing of a tennis racquet or other club, bat orother sporting device. As used herein, the term “sporting device”includes any physical object that may be used or implicated during aspecific sport. Exemplary sporting devices may include, but are notlimited to: golf balls, basketballs, baseballs, soccer balls, footballs,powerballs, hockey pucks, weights, bats, clubs, sticks, paddles, mats,and combinations thereof. In further embodiments, exemplary fitnessdevices may include objects within a sporting environment where aspecific sport occurs, including the environment itself, such as a goalnet, hoop, backboard, portions of a field, such as a midline, outerboundary marker, base, and combinations thereof. In this regard, thoseskilled in the art will appreciate that one or more sporting devices mayalso be part of (or form) a structure and vice-versa, a structure maycomprise one or more sporting devices or be configured to interact witha sporting device. For example, a first structure may comprise abasketball hoop and a backboard, which may be removable and replacedwith a goal post. In this regard, one or more sporting devices maycomprise one or more sensors, such one or more of the sensors discussedabove in relation to FIGS. 1-5, that may provide information utilized,either independently, or in conjunction with, other sensors, such as oneor more sensors associated with one or more structures. For example, abackboard may comprise a first sensors configured to measure a force anda direction of the force by a basketball upon the backboard and the hoopmay comprise a second sensor to detect a force. Similarly, a golf clubmay comprise a first sensor configured to detect grip attributes on theshaft and a second sensor configured to measure impact with a golf ball.

Sporting devices may comprise a removable sensor, such as anaccelerometer module that is configured to detect acceleration. Theaccelerometer module may be replaced with a different sensor (i.e.,pressure sensor). Using removable sensors may permit a sensor to be usedwith several different devices, such as soccer balls, powerballs,footballs, and/or allowing a user to upgrade or replace a faulty device,without having to obtain a new sensor. In certain embodiments, placementof one or more sensors 201 may be configured so that the weights of theincluded sensors do not change the balance or center of gravity of thesporting device.

In certain embodiments, one or more sensors may be held, attached orworn by a user. Exemplary “personal” devices may include, clothing suchas shoes, shirts, shorts, gloves, hats, or electronic devices, such aswatches, phones, and media players, among others. In one embodiment,sensors may be attachable to a user's shoe. In another embodiment, adevice may be attachable to a user's arm, such as similarly performed bya watch, ring, or graspable by a hand, such as any handheld electronicdevice, including mobile terminal devices and/or personal media players.Those skilled in the art will readily appreciate, with the benefit ofthis disclosure, that one or more personal devices may comprise asporting device, or any other component herein. Likewise, one or morestructures may include or be configured to interact with one or morepersonal devices.

Triggering events may be utilized in triggering the capture of imagedata of an athlete performing the physical action. FIG. 7 provides anillustrative flowchart of one method that may be performed, such as partof block 602 of FIG. 6, or separate from block 602. Looking to FIG. 7,decision 702 may be implemented to determine whether to initiate atriggering event. The inputs to decision 702 or any other decisionherein may be based on, inter alia, a user input, a sensor value, andcombinations thereof. For example, in one embodiment, a triggering eventmay be configured to instruct or indicate to the athlete to initiateperformance of a physical activity (see, e.g., block 704). Thus, whetherto implement a triggering event and/or what trigger(s) may be utilizedas part of the triggering event may depend on the physical activity,location of the trigger and/or user, a user input, predefinedcomputer-executable instructions located on a non-transitorycomputer-readable medium, or combinations thereof. Although flowchart700 is shown as beginning with decision 702, those skilled in the artwill appreciate that flowchart 700 is not required to be initiated withdecision 702 or any other decision. Further, decision 702 or any otherdecision or block disclosed herein may be implemented, either partiallyor in whole, before, after or during any other processes disclosedherein unless prohibited by the laws of nature.

A trigger (whether utilized in block 704 or any other process or systemdisclosed herein) may be audio, video, tactile, or combinations thereof.Indeed, those skilled in the art will appreciate that any human-sensibletrigger may be utilized in accordance this disclosure. The trigger mayindicate or instruct the user to perform a predefined physical activity.For example, a user may be instructed to initiate a 200 meter dash uponseeing a flash from an electronic device. In yet another embodiment, auser may be instructed to perform a drill specific to a certain sportupon hearing an audible cue. The trigger itself may provideinstructions, yet in other embodiments; the user may be informed of whatactivity to conduct prior to receiving the trigger. In this regard, asimple flashing light or an audible noise may suffice in certainembodiments. In one embodiment, the human-sensible trigger istransmitted from a device operatively connected to a first camera thatis configured to capture at least one image of the user performing thephysical activity. Those skilled in the art will further realize thatmultiple triggers may be utilized within a single process.

At least one of a plurality of triggers may be of a different type thananother trigger. For example, a first trigger may be an audible triggerand a second trigger may be a tactile trigger. As another example, afirst trigger may be a first audible trigger and the second trigger maybe a different audible trigger, such as by a different sound, pitch,volume, duration and/or combinations thereof. Further, differenttriggers may be implemented at different times and/or utilized tosolicit different actions from the athlete. For example, a first trigger(such as implemented at block 704) may be configured to prompt theathlete to initiate performance of a first predetermined physicalactivity. In yet another embodiment, a second trigger may be implementedto instruct or cue the athlete to perform a second physical activity. Aprocess similar or identical to block 704 may be implemented toimplement the second trigger, including being based upon a decision(such as decision 702). In one example, to indicate to the athlete toperform a predefined movement during performance of the physicalactivity, a second trigger (which may resemble or be identical to thefirst trigger being implemented for a second instance) may beimplemented to cue or instruct the athlete to perform a predefinedmovement during performance of the physical activity. Similarly, atrigger flag may be associated with a second image (or plurality ofimages). In one embodiment, second trigger flag may be with an imagewithin the plurality of images that correlates to the timing of thesecond triggering event. One or more flags may be associated with theathlete's performance of activities responsive to the trigger(s). Suchflags may be associated with images based upon perceived motions oractions determined from the pixel data. Exemplary methods of processingimages are described herein, including but not limited to blocks 604 and606 of FIG. 6 and 804 and 806 of FIG. 8. Those skilled in the art willappreciate other implementations are within the scope of thisdisclosure.

In certain embodiments, the capturing of image data (such as part ofblock 602 of FIG. 6, block 706 of FIG. 7, or any other process) may beresponsive to a trigger (such as a trigger implemented as part offlowchart 700). For example, the trigger may be received or otherwisesensed by an electronic device. In one embodiment, an image-capturingdevice configured to capture image data of the athlete may detect,sense, and/or measure a trigger and, in response automatically initiatecapturing images (See, e.g. block 706). In other embodiments, at leastone image is captured before at least one triggering event. This may beuseful, for example, to determine if a user “jumped” the trigger, suchas in anticipation of a trigger. Regardless of whether image data iscaptured before or after the triggering event (e.g., block 706), atrigger flag may be associated with an image within the plurality ofimages (e.g. block 708). For example, a non-transitory computer-readablemedium may comprise computer-executable instructions, that when executedby a processor, are configured to associate a trigger flag correlatingwith the timing of the triggering event with corresponding image data.Those skilled in the art will appreciate that there are many ways toflag or otherwise mark electronically stored image data; therefore, theyare not explained in further detail here. As explained in more detailbelow, one or more trigger flags may be utilized in the determination ofone or more athletic attributes.

Further aspects of this disclosure relate to processing image data, suchas the image data captured as part of block 602. As discussed above, thecapturing and/or receiving of the data may be conducted in real-time.Further embodiments also encompass the real-time processing of imagedata. As one example, block 604 may be initiated to process at least aportion of the plurality of images to identify image data of the firstathlete performing a first feature of a first athletic movement duringthe physical activity. In certain embodiments, a location of a bodyportion of the athlete, or a location of a sporting device within theimage data (absolute location or relative to another object, such as theathlete any other object represented by image data) may be used todetect the performance of one or more features of specific movements.For example, if the physical activity is a golf swing having an upswingathletic movement and a subsequent downswing athletic movement, anexample detection may comprise detecting pixel data indicative that agolf club is within a first distance from a ground surface. In anotherembodiment, image data that the athlete is performing the second featureof the upswing athletic movement is detected from pixel data indicativethat the golf club is within a second distance from a ground surface.

In yet other embodiments, an indication that a feature is beingperformed (or has been performed) may encompass the detection of amotion parameter. For example, at least one of a velocity value or anacceleration value may be utilized to determine initiation or occurrenceof a feature (or indicate the likelihood that a feature will beoccurring soon). Motion parameters may be determined entirely from theimage data (such as, for example, determining pixel data changes betweendifferent images). In other implementations, motion parameters may bedetermined without using the image data. For example, one or more of thesensors described above in relation to FIGS. 1-5 may be utilized, aloneor in combination with other sensors. In still yet further embodiments,one or more motion parameters may be determined from both image data andother sensor data. Those skilled in the art will readily appreciate thatlocation, motion data, sensor data (both image and non-image based) maybe used to detect the occurrence of a feature within an athleticmovement (or the athletic movement itself).

FIG. 8 is a flowchart 800 of an example method that may be utilized todetect on or more features or athletic movements in accordance withcertain embodiments. In certain embodiments, one or more elements offlowchart 800 may be implemented as part of block 604 of FIG. 6. In yetanother embodiment, one or more elements of flowchart may be implementedentirely independent of block 604. In accordance with certainembodiments, image data may be processed to determine whether one ormore movements of objects represented by image data meet a thresholdcriterion (See, e.g., block 804/806). Exemplary criterion may include amovement criterion and a movement quality criterion (See, e.g., block804 and 806, respectively). In one embodiment, a first criterion, suchas a first movement threshold criterion, may serve as a filter thatidentifies certain images that may be of interest and the secondcriteria further identifies what data (which may be within the samegroup) fits a more stringent criteria. The second criterion may be amovement quality threshold (See, e.g., block 612). In yet anotherembodiment, the first and second criteria may be conducted independentlyand in yet further embodiments, only one of a plurality of criteria maybe utilized. In certain embodiments, criteria may include one or moremovement threshold criterion, one or more threshold quality thresholdcriterion, and/or other criteria.

In one implementation, block 804 may be implemented and the outcome ofblock 804 may be used, at least in part, as a determination of whetherto implement (or how to implement) block 806 or other process. In yetanother embodiment, the first and second criteria may be conductedindependently. For example, blocks 806 may be implemented simultaneouslyor at different times regardless of the outcome of each other. In yetfurther embodiments, only one of a plurality of criteria may beutilized. For example, only one of blocks 804 and 806 (or a portionthereof) may be implemented.

As one non-limiting example, block 804 may be implemented to processimage data to identify data meeting a movement threshold. In oneexample, one or more of the plurality of received images may be utilizedto identify a first range of images satisfying at least a first movementthreshold. Image data (which may comprise whole or portions of images)may be analyzed to identify a first threshold level of movement of anobject represented within the image data. The object may be a sportingdevice, such as a ball, bat, puck or glove. The object may also be theathlete or portion of the athlete. In certain embodiments, pixel datamay be analyzed to identify a quantity of pixels in a portion of thecaptured images satisfying a first threshold level.

The threshold level may be configured to be indicative of a movement ofan object. As non-limiting examples, one or more thresholds utilized aspart of block 804 or any other process described herein may be tied tohorizontal movement (e.g., running) or vertical movement (e.g., dunkinga ball), or both. This threshold level can be entirely different thanone or more additional threshold levels disclosed herein. For example, afirst movement threshold may be triggered by the athlete's arm movementand a second threshold may pick specific movements tied to another bodypart or region, such as the other arm, a leg, etc. As another example, afirst movement threshold may be associated with a golf club head whileanother is triggered by the athlete's arm movement. In one embodiment,the first threshold may detect whether a first body portion moved and/orwhether a body portion moved along a specific axis. As used herein, a“body portion” may be any one or more sections, areas, systems, orportions of the user's body represented within image (e.g., pixel) data.In one embodiment, the image data may correlate to a single appendage(e.g., a leg or arm), group of appendages (e.g., an arm and leg or twoarms), or portions thereof. In certain embodiments, the body portion maycorrespond to a portion of multiple appendages, such as the upper legand/or inner arm areas, yet in other embodiments, the portion is devoidof appendages. In other embodiments, a first region (e.g., an upperregion) may be distinguished from another region (e.g., a lower region).Those skilled in the art with the benefit of this disclosure willappreciate that any portion of the body represented by image data (suchas at least one pixel) may serve as a “body portion” in accordance withcertain embodiments. Further discussions of threshold levels will bediscussed below, including with reference to movement quality thresholdsin relation to block 806. Those discussions are incorporated herein andthroughout this disclosure.

In one embodiment, at least a portion of the image data, such as aplurality of images or portions thereof, may be processed to identify aninitiation image (see, e.g., block 804 a). In one embodiment, theinitiation image may be the frame or image in which a feature is firstidentified. In one embodiment, it may be an image in which the athletefirst moves. In yet another embodiment, the initiation image may be theimage in which a game or activity is initiated, regardless of whetherthe user moves. For example, in one embodiment, movement of anothersprinter may signal the beginning of an event. In another embodiment,seeing a waving flag indicating an event has been initiated, or a gunemit smoke from being fired as well as other actions capturable by animage may be used to indicate an initiation image in accordance withvarious embodiments. In one embodiment, the first criterion may bedirected towards movements associated with the specific athlete. Incertain implementations, the initiation image is determined based upon auser input, such as a user selecting a UI element indicating theinitiation image. For example, a user recording the athlete may want toflag an initiation image in real-time as the athlete is performing aspecific action. For example, an image just prior to a basketball playerattempting to dunk the ball may be identified as an initiation image. Incertain embodiments, identification of the initiation image may resultin capturing the image data at a different frame rate. Those skilled inthe art will appreciate that other non-movement events may also be usedin conjunction with certain embodiments. For example, one or moresounds, tactile inputs, or other information (including but not limitedto those described above in relation to FIGS. 6 and 7) may be utilizedin conjunction with one or more embodiments. A second movement thresholdmay be implemented to detect whether the movement met a thresholdcriterion.

In certain implementations, landmarks/distance calibrations may beutilized from time-stamped image data to allow for precise measuring ofperformance. For example, objects represented by image data may beutilized to determine whether movement thresholds are met (e.g., block804 b). For example, markings on a field (such as yard lines) may beused to calibrate distance measurements. In certain embodiments, objectsmay be identified and upon identification, used in calibrationprocesses. For example, many sporting fields, tracks, courts, and thelike have fixed dimensions. Likewise, basketball hoops, goalposts, goalnets, and other objects are often sized to specific known dimensions.These dimensions may be used to identify thresholds and/or determinewhether certain thresholds have been met, including but not limited to:flight time for vertical jump, distance for throws, kick distance andpower, among others, sprint times between two distances. Suchcalibration techniques are not limited to stationary objects. Forexample, balls, pucks, and other sporting devices may be used tocalibrate distances. In this regard, a basketball has a known shape andsize. Such dimensions may be used to calibrate measurements. Althoughthese calibration techniques have been described in relation to block604, those skilled in the art will appreciate that such techniques arenot limited thereto, but instead may apply to any system and methoddescribed herein, including block 806. Further aspects of thresholds aredescribed immediately below.

Certain systems and methods may comprise the utilization of decision 606to determine whether additional data is required, such as whethermultiple thresholds or criteria are met. For example, looking again toFIG. 8, block 806 of flowchart 800 may be implemented to determinewhether image data (e.g., pixel data) satisfies another threshold, whichmay be unrelated to the movement threshold(s) of block 804. Thus, block804 may be executed independently of block 806 and vise-versa. Incertain embodiments, one or more processes of block 806 shown in FIG. 8may be implemented in a parallel or serial fashion with respect to block604 shown in FIG. 6. In one implementation, block 806 may identify afirst body portion of the athlete that satisfies a first movementquality threshold. Further, it will be appreciated by those of skilledin the art that portions of various blocks, such as 804 and 806, may beimplemented independently of other components. For example, sub-block804 a may be performed entirely separate from block 804. Further, it isto be understood that in alternative embodiments, one or more portionsof blocks 804 and 806 (or any other block of FIG. 8) may be combined.For example, sub-block 804 a may be utilized as part of block 806 andone or more of sub-blocks 806 a-c may be utilized within block 804.

The selection and/or utilization of the one or more portions of theathlete's body represented within the image data may be based on thepredetermined physical activity, user input, historical data, andcombinations thereof among others. In one embodiment, block 806 maycomprise one or more sub-parts that may be conducted independently ofeach other, yet in other embodiments may be at least partially dependenton another subpart of block 806 or another mechanism. For example, thepredetermined physical activity may be used (either in whole or in part)to select which body portion(s) are utilized and/or whether the movementof the portion(s)—as represented within the captured image data—meet aquality threshold (see, e.g., blocks806 a and 806 b). As one example ofidentifying a body portion in block 806 a, a first embodiment mayutilize the image data associated with the athlete's legs, such as ifthe predetermined physical activity comprises or consists of a 200-metersprinting event. Yet another embodiment may utilize image dataassociated with at least a portion of the athlete's legs as well astheir arms. In yet further embodiments, a user input may be optionallyprovided to select which image data is utilized. A user input may beconfigured to select an option from a plurality of options, yet in otherimplementations a user may select any portion or part to be utilized.

Systems and methods may be implemented that utilize a different bodyportion or object represented within the image data based uponcharacteristics of the image data itself. For example, pixel datarepresenting an athlete located at a first distance from the camera maybe more accurate and/or precise than pixel data representing the sameathlete located at a second distance that is further than the firstdistance with respect to a camera that captured the image data. Further,zooming, lighting conditions or other parameters may alter the qualityof the captured image data as the athlete performs the athleticactivity. Therefore, selecting a portion (e.g., 806 a) and/or a qualitythreshold (e.g., 806 b) may be based on a myriad of factors, some ofwhich may be weighted more than others. In certain embodiments,selecting and/or switching which portion of the image data is utilizedin one or more processing steps may be automatic, such that the athleteor operator of the camera does not have to make the selection. It may beperformed in real-time, such that the selection and/or switching ofobjects represented in the image data as the data is being captured.

As another example, the athlete may travel throughout a 4-dimensionalspace during performance of the activity. Therefore, the camera(s)perspective of the athlete may be altered during the capture of theimage data. In other embodiments, multiple cameras (which may havediffering capabilities) may provide image data. These and othervariables may result in different portions to be utilized or qualitythresholds to be determined. For example, in one embodiment, image datacomprising a sprinter running at a first distance may utilize, at thevery least, image data comprising pixels representing the athlete's legs(or a portion thereof). However, as the user travels further away fromthe image capturing device, the number of pixels representing theathlete's legs (or portion thereof) may decline, therefore, in oneembodiment, another body portion may be utilized to compensate for thisreduction of pixel data. As one example, decision 808 may be implementedto determine whether to alter, update, switch or otherwise adjust theportion(s) of the athlete represented by pixel data utilized (e.g.,block 806 a) and/or how they are utilized (e.g., block 806 b). Incertain embodiments, block 806 may be implemented to determine whetherto adjust parameters associated with a movement threshold of block 806and/or block 806, and/or other thresholds.

For example, as a non-limiting example of adjusting one or moreparameters of block 806, pixel data from an athlete's legs may beinitially utilized, such as via block 806 a, to identify image data fora first movement quality threshold; however, pixel data from theathlete's arms may supplement or replace the utilization of the pixeldata representing the legs (such as via block 806 a). Thus, in certainembodiments, the selection and switching of body portions or objectsutilized may be an iterative process. Further, the threshold levels forone or more of these body “portions” may be altered based upon thequality of the image data for different images. In certain embodiments,a movement quality threshold may compare movement of multiple portionsof the athlete's body and determine whether two or more portions move inrelation to each other. For example, arm swing data may be compared withleg movement data to determine which most accurately reflects thepredetermined physical activity.

In accordance with one embodiment, image data representing the relevantbody portions (such as from block 806 a) may be identified. Image datarepresenting the relevant body portions may be isolated. In certainembodiments, surrounding pixel data may be utilized. Yet in otherimplementations, entire frames of image data may be utilized todetermine if one or more threshold limits have been met. In certainimplementations, an optical flow algorithm may be utilized to analyzethe image data (e.g., pixel data) and determine movements of the bodyportions. In this regard, one or more image capturing devices maycapture images at different or variable frame rates. For example, animage capturing device may capture images at a variable rate between 30to 240 frames per second (fps). Therefore, determinations of movementmay utilize rate of capture information to accurately determine timeintervals between frames of data that may be separated by uneven periodsof time. As another example, a first image capturing device may captureimages at a rate of 100 fps and a second image capturing device maycapture image data at a rate of 70 fps. Thus, data from these two imagecapturing devices may be normalized to account for variations in timebetween pixel movements. In one embodiment, at least a portion of theplurality of sequential images each represent about 1/60th of a second,yet in another embodiment, at least a portion of the plurality ofsequential images each represent no more than 1/60th of a second.Because several frames of data may be captured and analyzed every secondin some embodiments, real-time analysis can be provided to the athletewithout substantial delay. In certain implementations, accurate timebetween an image having the first frame rate an image having the secondtime frame may be determined. This accurate time may be utilized in oneor more processes. In certain embodiments, data from two images may beprocessed to determine movement between two frames of data. In oneembodiment, pixel movement may be interpolated from two subsequentimages. In certain embodiments, multiple cameras may be utilized. As oneexample, two cameras having the same frame rate may be configured tohave a synchronized offset. Using a synchronized offset may allow ahigher effective frame rate to be obtained. For example, if a firstcamera is set to 50 fps and captures images starting 1/100th of a secondbefore a second camera also set to 50 fps, then collectively, theseimages from these two cameras may be utilized to obtain an effectiveframe rate of 100 fps. Using multiple cameras may also be utilized tocorrect any incorrect data in accordance with certain embodiments. Forexample, a first camera configured to capture 50 fps may only capture 48or 49 fps and thus data from a second camera may be used to provideaccurate image data during the relevant time period.

Using the identified parameters, image data (e.g., pixel data) isutilized to determine that a first body portion movement qualitythreshold is met (see, e.g., block 806 c). In one embodiment, image datarepresenting the human form may be utilized to identify pixels or otherimage data representing the athlete. If multiple athletes are presentwithin the frames, the specific athlete of interest may be isolated. Inone embodiment, the athlete may be isolated based upon known parametersof the athlete (e.g., height, weight, color of clothing). In anotherembodiment, a user input may indicate which pixel data represents theathlete. In yet further embodiments, the athlete may wear a detectablemarker configured to be detectable by at least one electronic device.Those skilled in the art will readily understand that these are merelyexamples.

Certain implementations may weigh one or more parameters resulting fromthe optical flow algorithm or other processes utilized to determineimage data movement, such as movement of pixels. In this regard, aspectsof this disclosure relate to novel motion entropy algorithms In certainembodiments, data from pixel movements between a plurality of images maybe utilized to identify types of motion. As one example, data providedor derived from an optical flow process may be used. Example data mayinclude the pixel-distance change of an identified object from one frameor image to another frame or image (sometimes referred to in the art asthe “flow field”). These may be utilized in parameters that identifyspecific types of motion. In certain embodiments, these outputs may beused for segmentation and motion identification. In one embodiment,large-scale motion may first be identified and more detailed motions maythen be identified. As an example, a first process may determine that anathlete is running and, in response, one or more processes may then beused to specifically detect hand motion and characterize that. Othermotions that may be identified or derived include: initiation of theactivity, acceleration, velocity, reaction, tempo, distance travelled byan object, or completion of the activity. Further embodiments mayutilize one or more processes to determine which of segmentation,scaling, or other features may be implemented, or the extent they areutilized.

These or other processes may be used to provide an output concludingthat a particular motion was occurring at the respective frame(s). Inone embodiment, an athletic movement (or feature of a movement) may bedetected from a motion parameter based on at least one of a velocityvalue, an acceleration value, a location of a body portion of theathlete, or a location of a sporting device within the image data.Determinations that a threshold is met may be based, at least in part,on the motion parameter. For example, the determination of the motionparameter is determined based upon, at least in part, determining that avelocity value or an acceleration value meets a first threshold. One ormore of these attributes may be determined entirely from the image data.However, as discussed above, other sensor data may be used, eitherindependently or in conjunction with image data.

In this regard, aspects of this disclosure relate to identifying imagedata (such as but not limited to specific images) that correlate to aspecific physical movement or activity of the athlete (e.g., block 810).For example, certain embodiments may detect initiation of the athleticactivity, performance of an athletic movement, and/or the occurrence ofa movement feature. As non-limiting examples, image data may be used toidentify one or more actions, including: initiation of the activity,levels of acceleration, velocity, reaction, and/or tempo, distancetravelled by an object, completion of the activity, among others. Asdiscussed above, objects (either stationary or in motion) may beutilized to calibrate measurements, including those relating to movementquality thresholds.

Thus, block 810 may be implemented to identify image data (includingspecific frames or images) such as including, but not limited to: aninitiation image, a termination image, or any other image comprisingmotion data that can be identified based upon the systems or methodsdisclosed herein. An initiation image and/or a termination image may beidentified for one or more athletic movements, athletic features of amovement, or combinations thereof. As one example of an embodiment thatutilizes blocks 806 and 810, block 806 may be utilized to determinewhether pixel data is altered between two subsequent images such thatthe alteration satisfies a specific first body portion (e.g., upper arm)movement quality threshold. As described above, image data between twosuccessive images may be interpolated or otherwise derived from existingimage data. Thus, based upon the first body portion quality thresholdbeing met, the respective image in which it first occurred may beidentified or flagged as an initiation image. In one embodiment, animplementation of block 810 may utilize subsequent images following whatmay be deemed an initiation image in any athletic determinations. Forexample, if analysis of a plurality of subsequent frames further revealthat the athlete is engaged in a specific activity, then one embodimentmay analyze past frames (or portions thereof) to identify where thespecific action began. Because multiple frames may be captured within asecond, certain embodiments may analyze tens of images without unduedelay. Yet in other embodiments, systems and methods may identify theinitiation image (or other image) based solely on that image and/orimages preceding that image. Similarly, a termination image may beidentified based upon a certain threshold (or plurality of thresholds)not being met. In other embodiments, a termination image may beidentified based on a second threshold being met, such as for example adifferent body portion movement quality threshold. In accordance withone embodiment, movement of an athlete's torso may be used asidentification of an initiation image (e.g., block 804 a) of a baseballplayer pitching a ball, while a movement quality threshold relating tothe quality of movement of the athlete's throwing arm may be used todetermine that the athlete is pitching the ball and/or released the ball(e.g., block 806). In certain embodiments, image data indicating thatthe ball struck a catcher's mitt or a bat may signify the terminationimage of the pitch. Other thresholds, however, such as, but not limitedto, one described in block 804 may also be utilized, either alone or incombination, with a body movement quality threshold.

Thus, image data, alone or in combination with other sensor data, may beutilized to identify a performance attribute of the athlete. As oneexample, an initiation image of a feature (alone or in combination withanother image) may be used to determine at least one performanceattribute of the athlete. Example attributes may include, but are notlimited to: speed, reaction, endurance, and combinations thereof. Inanother embodiment, a completion image comprising image data of theathlete completing the feature (which may be identified at block 810from data obtained at one or more processes of block(s) 804 and/or 806may be utilized. In one implementation, physical activity duration basedupon the initiation image and the completion image may be calculated.Such information may be used to determine velocity, acceleration, tempo,pace, or a combination thereof. As will be explained below, suchinformation may also be used in one or more calculations relating to aperformance rating.

Determinations of an attribute may utilize data obtained from one ormore other sensors that are not used to capture the image data. Inaccordance with certain embodiments, alterations of the image dataresponsive to external stimuli may be considered. In one embodiment,flagged images associated with triggering events may be utilized. As oneexample, a reaction value for the athlete may be determined based uponthe duration of time between the image associated with a trigger flagand the initiation image. For example, an external stimulus, such as anaudible or visual cue, may indicate the start of a race and accordingly,the associated image(s) may be flagged as being correlated to a firsttriggering event (e.g., block 708). Based upon one or more thresholdsbeing met, such as described herein (e.g., blocks 804 and 806), it maybe determined that a user has initiated a predetermined activity. Incertain embodiments, the activity may be a sport-specific activity.Thus, the user's reaction time may be determined from the flagged imageof the triggering event and the initiation image.

As discussed above in relation to block 704, one or more triggeringevents may occur before, during or after the athlete's performance ofthe physical activity. In one embodiment, a second triggering event maybe utilized to indicate to the athlete to perform a predefined movementduring performance of the physical activity. A second trigger flag maybe associated with an image that correlates to the timing of the secondtriggering event (such as block 708 or another process). Another flagmay be associated with an image correlated to the athlete performing thepredefined movement. In one such embodiment, a second reaction value forthe athlete based upon the duration between an image associated with thesecond trigger flag and an image correlated with the athlete performingthe movement may be calculated.

In further embodiments, sensor data (inclusive of non-image sensor data)may be utilized in any determinations, derivations or calculationsdescribed herein. Sensor data may be captured from sensors including,but not limited to: a wrist-worn sensor, a footwear-worn sensor, aportable entertainment electronic device, and combinations thereof. Inaccordance with one embodiment, sensor data may be utilized to conductimage stabilization upon at least a portion of the plurality of images.In one implementation, sensor data may be received from a sensoroperatively attached to the athlete and used for image stabilization,identification of the athlete from an plurality of objects within thecaptured image data, determinations of when to capture images,determinations of what image data to process, and/or other utilizations.

Further aspects of this disclosure relate to transmitting feedbacksignals to the athlete (e.g., block 608 of FIG. 6). The feedback signalsmay be based on the detected athletic data and/or optimal timing forcertain athletic movements based upon the athletic data. As used herein,a feedback signal may be audio, visual, and/or tactile, such as avibrating or pulsing tactile device, an optical device (e.g. LED orother light) that blinks, changes color, alters brightness, etc., anaudio device that may emit a sound, such as ticks, beeps, and/or musicor other audio effects that may contain rhythmic properties, becontinuous, sequential, and/or exhibit other properties. As non-limitingexamples, certain embodiments may utilize electroactive polymers (EAPs)that provide haptic feedback and/or vibration motors. In certainembodiments, one or more feedback devices may be worn on (or otherwisein contact with (directly or indirectly) with the body. The feedback maybe adjustable and/or controllable.

Using flowchart 800 of FIG. 8 as one example, block 812 may beimplemented to transmit a real-time feedback signal to the athlete. Thefeedback may be transmitted in response to identifying the performanceof an activity (e.g., swinging a club), movement of an activity (e.g.,the backswing) or feature of a specific movement (e.g., initiating thebackswing, or speed/location of the club during a backswing, orcombinations thereof. For example, in one embodiment, determination thata threshold was met or position for the body or equipment was reached(such as part of block 702) and/or that image data was correlated to aspecific movement (such as part of block 810), may result in adetermination that a first feature of a backswing is or has justoccurred. As one example, the position of some part of the body, or theposition/3D orientation of the equipment in use, if any, could be atrigger for the feature determination. Based upon the determination, afeedback signal, such as an audible tone, may be transmitted to theathlete.

Many athletes will desire to know more than just a single data point(such as when a feature is initiated or ended). In this regard, usingmultiple data points may be more beneficial in many instances. Usingmultiple data points, such as for example, detecting multiple featureswith a movement) and transmitting feedback to the athlete that allowsdistinction between the different features may be greatly beneficial.For example, one aspect that can greatly affect a golf swing (or anyother action such as a tennis swing) is the speed of the swing itself.Swings that are too slow can result in less energy transfer to the ball,and swings that are too fast may cause the golfer to lose control andconsistency in the swing. The “tempo” of the swing, or in other wordsthe timing of the backswing and forward swing, can also have a profoundeffect on the speed and consistency of the swing, as well as otheraspects of the swing.

Therefore, block 812 may be initiated (or repeated based upon imagedata) to transmit an audio feedback tone at various frequencies toprovide feedback on the tempo of the golf swing. For example, decision814 may be implemented to cause the transmission of multiple feedbacksignals that are based upon real-time data. In certain embodiments,previously recorded data may be analyzed. Image data may detect features(e.g., based upon speed, acceleration, and/or location of the clubduring a backswing), and as a result, different tones (or frequencies ofthe tone) may be transmitted to provide an indication of tempo.Different athletes may have different optimum swing tempos. Thus,providing a generic tempo to mimic may not assist the athlete. In thisregard, a single golfer may even have different optimum swing tempos fordifferent clubs. For example, a golfer may have one optimum swing tempofor a driver or other wood club, another for long irons, another forshort irons, and another for putting. However, it can be difficult for agolfer to determine his/her optimum swing tempo(s), and it canadditionally be difficult for a golfer to maintain the optimum swingtempo(s) during practice and/or play.

Rather than attempting to fit every athlete into a one-size-fits-allapproach, providing real-time feedback based upon, at least in part,image data of the athlete's own performance more readily allows theathlete to improve. For example, in certain embodiments, after sending afirst audio feedback signal (or any other type of feedback signal) inreal-time based upon detection of a first feature, a second audiofeedback signal based upon the movement properties of a second featuremay be transmitted, such that the athlete receives audio feedback duringperformance of the athletic movement configured to provide audible tempofeedback in regards to the athlete's performance of the first and secondfeatures of the athletic activity.

In this regard, example embodiments contemplate capturing movementassociated with an activity (e.g., constituent movements and/or one ormore components thereof) via video or image sequences to obtain imagedata, analyze that image data, which analyzed data is an input to afunction that translates the analyzed data to feedback provided to theuser. The feedback is directed to enable the user to “groove” theirmovement(s) in an activity, e.g., to groove their own swing. To “groove”implicates that the user is, generally, neither seeking to duplicate themovement(s) (e.g., swing) of another participant (e.g., a pro) nornecessarily seeking to attain some theoretical or ideal movement (e.g.,such ideal may simply not be physiologically attainable for such user).Rather, the user is seeking to find and internalize the movement(s)(e.g., a swing) that is natural to themselves, including enablingconsistent reproduction of the “grooved” movement(s). The groovedmovement may be time bound, i.e., applicable as to the user's currentcircumstances.

Those skilled in the art will appreciate that the feedback signal may betransmitted by any electrical, mechanical, or electro-mechanical device.In one embodiment, an electronic device that includes a memory storingcomputer-executable instructions and a processor in communication withthe memory, such as described in relation to FIGS. 1-4 may be utilized.A processor may be configured to execute computer-executableinstructions on a non-transitory computer-readable medium to perform anumber of actions. The device (e.g. the processor) may receive an inputof a specified feedback signal or signals (e.g., a plurality of audiosignals as the data is analyzed) and identify an audio tone or file forthe feedback signal(s). Thus, in certain embodiments, a plurality oftones exhibit a tempo that is correlated to a tempo of the athlete'smovement. Thus, certain aspects relate to a tempo indicating device forproviding the feedback signal. The tempo indicating device may includean input for receiving information to output, an output configured toemit one or more different types of feedback signals.

In one embodiment, a tempo indicating device may be any device that isconfigurable to emit a sequence of regular, metrical beats to a user,also referred to as a rhythm, in a format that is recognizable to theuser. For example, the format for emitting the rhythm may include:audio, visual, and/or tactile, such as a vibrating or pulsing tactiledevice, an optical device (e.g. LED or other light) that blinks, changescolor, etc., an audio device that may emit a rhythmic sound, such asticks, beeps, etc., or music or other audio effects that may containrhythmic properties. The tempo indicating device may be adjustableand/or controllable to change the tempo (i.e. beat frequency) of therhythm that is emitted to the user, such as based upon the detectedathletic data. As one example, a first audio feedback signal may be afirst audible tone at a first frequency and systems and methods may beemployed for generating the second audio feedback signal by modulatingthe audible tone to a second frequency.

Further aspects of this disclosure relate to providing feedbackregarding proper or optimal timing of events based upon detectedathletic activity data (see, e.g., 816). For example, one or more of theabove-mentioned systems and methods may be used to first identifyaspects of the athlete's activities. Using a golf swing as an example,image processing methodologies (alone or in combination with data fromnon-image based sensors) may be used to detect the timing and/or tempoof the athlete's backswing and/or forward swing. In this regard, exampleembodiments contemplate capturing, during the activity, constituentand/or components (e.g., a golf swing), data from wearable sensors, suchdata being employed in a “sensor fusion” (e.g., to provide synergisticfeatures/functionality) so as to enhance analysis of the acquired data(e.g., image data) and, in turn, enhance the feedback to the user (e.g.,by more accurate or beneficial audio feedback).

Feedback systems may be implemented to provide feedback signals to theathlete as discussed above, such as to indicate the tempo of the golfswing. However, in additional embodiments, based upon the detection oneor more features of the backswing or forward swing, an additionalfeedback signal may be transmitted at a predetermined time configured toindicate the proper timing for the athlete to perform an additionalfeature of the athletic performance, such as making contact with theball. The transmission and/or attributes of the additional “optimaltiming” feedback signal may be based upon the occurrence of one or morefeatures of a movement. In certain embodiments, features of a backswingmay be utilized to determine when (or even whether) to transmit theadditional feedback signal of the additional feature (e.g., makingcontact with the ball). Thus, an athlete may receive feedback, such asvarious audible tones) indicative of the tempo of their backswing andtheir forward swing, and despite the tempo of the forward swing, anadditional feedback signal may mark the timing of an optimal point intime to make contact with the ball, based upon properties the detectedbackswing. Yet, other embodiments may use data relating to multiplefeatures from different movements (e.g., both a backswing and theforward swing). Thus, certain embodiments may not only provide feedbackof the user's current athletic movement, but also feedback based uponproper and/or accurate timing events in view of the current athleticmovements.

As discussed herein, feedback generation systems and methods may includeaudio feedback. In one example, one or more tones may be assigned withoutput data associated with a plurality of swing features. The tones maybe assigned using any of various schema. As an example, an assignabletone may be associated with one or more velocities, accelerations,rotations, etc. associated with a feature. For example, each toneassignment may be based solely on one of a velocity, an acceleration, ora rotation. Alternatively, each tone assignment may be based on acombination of one or more of these, or other combinations.

As another example, each of a plurality of image or video frames mayhave an (assigned) number of tone units. Accordingly, if a feature isdetected in such image or frame, the feature's tone may be utilized forall such tone units. The tone assignments may be as to featuresgenerally or specifically. For example, if two features have the sameparameters as to the applied combination of velocities, etc., a generalassignment scheme may assign the same tone to both features, while aspecific assignment scheme assigns a first tone to one feature and asecond, different tone to the other feature.

In certain embodiments, more than one feature may be detected in anygiven image or frame of a swing's imaging. For example, for a firsttheoretical frame, a body rotation movement may be detected along with aclub movement. Accordingly, as to feedback associated with such image orframe, the feedback generator may assign a tone for each such detectedswing parameter (e.g., one for the body movement and one for the clubmovement). As such, that associated feedback may be a combination oftones. Indeed, from frame to frame, combinations of detected featuresmay change, such that the combination of tones may be varying.

As another example, feedback generation systems or methods may provide atone as feedback to the user for a predetermined feedback period. Thatfeedback period may be variously provided. As an example, the feedbackperiod may correspond to the time period of the image or frame in whichthe feature was detected; in that case, the tone may be provided for thetone units associated with such image or frame. As another example, thefeedback period may include not only the time period of such image orframe, but also some additional time period, e.g., a configured numberof subsequent, adjacent tone units.

In accordance with various embodiments, during any feedback period(whether or not including such subsequent tone units), the tone may besubject to a tone envelope. A tone envelope may include an attackperiod, a decay period, a sustain period and a release period (an “ADSRenvelope”). The tone envelope may also include a hold period: e.g., ifany image or frame exists in which no feature is detected (a “nullperiod”), one or more tones associated with the immediately prior imageor frame (or the next prior image or frame having a feature) may be heldas per the sustain period, so as to bridge the null period. A holdperiod may not be applicable to the initial image or frame.

In accordance with various embodiments, a combination of tones may bevariously implemented. For example, each tone of a plurality of tonesmay simply be combined with others for the duration of a feature. Insuch combination, each such tone has a given amplitude during itsrespective duration, and the overall amplitude is the sum of such tones'amplitudes. As an alternative, the overall amplitude may be subject to amaximum, such that tones may be combined so that each tone equallycontributes to such overall amplitude. As yet another alternative, tonesmay be combined with sonic adjustments that vary among the combinedtones. As an example, sonic adjustment may be based on priorities orother weighting responsive, e.g., to the (assigned) value of theassociated swing component, such value being, for example, related toresults. To illustrate, the tone of highest priority may be unchanged,while a tone of lower priority may be combined: at a priority-based,reduced amplitude relative to the highest priority tone; or the afteradjusting its harmonic content (with or without maintaining itsfundamental); or after changes to its ADSR envelope; or after changes inone or more other sonic features.

In certain embodiments, if the sonic characteristics associated with oneimage or frame are different than those of the subsequent image offrame, the transition there between may be conditioned so that, from auser-perception point of view, the transition is softened, smoothed orotherwise adjusted so as to enhance sonic appeal.

In certain embodiments, for a time period after the image or frameassociated with the final detected feature, the feedback generator mayprovide terminating feedback. Such terminating feedback may include thetone(s) of the last image or frame of a detected feature. As an example,such terminating feedback may be implemented via applying and/orextending a hold period (see, e.g., ADSR envelope, above). Suchterminating feedback may continue through any final imaging of the swing(e.g., even if no feature is detected in any images or frames of suchfinal imaging). Such terminating feedback may continue for a selectedtime after imaging of the swing.

The tones may be variously implemented and determined. Each tone may beimplemented via a system-determined fundamental harmonic and harmoniccontent. Moreover, the universe of user-available tones may beimplemented via sound synthesizer technologies, including samplingtechnologies. Such synthesizer technologies may be variouslyimplemented. As an example, the mobile app described above may includesuch technologies, together with a GUI that enables the user toselect/configure operation, such as, e.g., configuring features,selecting (or de-selecting) voices, setting amplitudes or changing ADSRand/or Hold Period parameters, sampling sounds, etc. These descriptionsas to feedback generation and administration apply to any feedbackdiscussed herein.

Further aspects relate to providing feedback to an athlete's based uponthe effect their athletic activity has on another physical object, suchas a sporting device. For example, feedback signals may be providedbased upon the trajectory and/or attributes of a golf ball's flightafter being contacted with the athlete's golf club. In anotherembodiment, a basketball player's shot may be used to provide feedbackto the player. In one embodiment, the athlete's effect on an object maybe determined (see, e.g., block 610). As one example, block 610 mayutilize one or more systems described in relation to block 604 and/or802 to process a plurality of images to identify image data of the firstathlete contacting (directly or indirectly) the physical object. Infurther embodiments, image data of an object in motion, such as afterbeing contacted, may be utilized. Motion data may be utilized even ifthe athlete is not within the image data. In yet further embodiments,non-image sensor data may be used to obtain motion data based upon anobject placed in motion or otherwise contacted by the athlete. Forexample, in one embodiment, a baseball may comprise an accelerometerthat may be used to determine speed, spin, acceleration, or other motionparameters of the ball after being thrown by a pitcher and/or struck bya batter. Data from the accelerometer may be utilized alone or inconjunction with image-based data. Likewise, sporting devices, such asthe batter's bat may comprise at least one sensor. In this regard,collecting and/or analyzing of the data of block 401 may incorporate anyand all systems and methods disclosed herein, including but not limitedto those described in FIGS. 68. In certain embodiments, the datacollected and/or analyzed as part of block 410 will be entirely distinctfrom the data collected that relates to the athlete performing a featureof an athletic movement (e.g., block 404). Yet those skilled in the artwill appreciate that in certain embodiments, block 410 may be utilizedto determine whether a feature or movement occurred and/or an attributeof a performed feature or movement. In this regard, certain embodimentsmay incorporate block 610 before or during implementation of block 608.

Upon determining the effect of the athlete upon the physical object,such via block 610, feedback signals may be transmitted to the athlete.In one embodiment, block 608 may be initiated (or modified) to providefeedback signals to the athlete. The feedback signals may be of the sameformat and type as feedback signals relating to the athlete'sperformance of a prior or concurrent feature or movement. For example,if audio signals were used to convey attributes of the athlete'sperformance, then audio signals may also be utilized to convey feedbackof attributes from the data relating to feedback of the athlete's effecton the physical object (which may be unrelated to the performance of afeature). In one embodiment, an audible tone may be modulated based uponattributes of a golfer's swing and a second audible tone may bemodulated based upon attributes of the ball upon being hit with theclub. In one example, a “sliced” ball may result in a first modulatedsignal and a “hooked” ball may result in the transmission of a secondmodulated signal. In certain embodiments, impact forces, speed,acceleration, location relative to a surface (such as the ground) orother attributes may be used in determinations of what feedback signalis utilized (and/or how a feedback signal may be altered based upon oneor more attributes).

Further aspects of this disclosure relate to calculating an athleticscore based upon the captured image data and/or data derived from theimage data. Example embodiments contemplate analyzing captured data, inany combination of image data, sensor data, or swing results data, so asto provide feed-forward, i.e., coaching. Such feed-forward may beprovided via a GUI of a portable electronic device, e.g., the GUI of anapp or any computer-executable instructions on a non-transitorycomputer-readable medium executing, for example, on a device, such asportable device 112, which may be a smartphone that provides the camera.E.g., feed-forward audio may be provided. Such feed-forward may bebeneficial to muscle memory training. Also, with a swing or otherconstituent being captured via an image sensor, the feedback that isgenerated for the athlete can be stored for replay with the storedvideo. This stored video may then be played back later, includingrepeatedly (e.g., if the swing had particularly good swing resultsdata), for the purpose of muscle memory development.

In one embodiment, a sport-specific algorithm may be utilized todetermine sport-specific score for the athlete. In one embodiment, areaction value derived, at least in part, from image data, andoptionally another performance attribute, may be utilized in asport-specific ranking algorithm to obtain a single athletic score forthe athlete. The score may correlate attributes of the athlete'sperformance (such as through data collected at blocks 604, 804 and/or806) with a result (such as data collected at block 610). For example, agolfer's swing data may be compared with attributes of the struck golfball. For example, certain tempos of a swing may be scored based uponthe athlete's effect on the golf ball. In certain embodiments, a scoremay be used to rank the athlete and a second athlete according to theirrespective athletic scores. In certain embodiments, a trainer, coach, orathlete may merely have to transmit image data (such as a video) of theathlete performing physical activity. A system may be configured toanalyze the image data (such as by implementing one or more of theprocesses described herein) to provide an athletic score. In oneembodiment, the image data may be parsed to identify predeterminedphysical activities represented within the image data. In furtherembodiments, systems and methods may utilize the performanceattribute(s), rating(s), and/or the image data to provide a trainingprescription.

Physical activities implicate motor coordination. Motor coordination isthe combination of body movements created with kinematic (such asspatial direction) and kinetic (force) parameters. Motor coordination isachieved by effecting, as to a participant's body and/or body parts, asequence of initial positionings/orientations, initial movements,subsequent parts of the initial movements, and subsequent movements.Motor coordination is enhanced by effecting such sequence in awell-structured manner, e.g., characterized by proper timing of an amongmovements, efficient movements, and smooth transitions between and amongmovements. Motor coordination, while fundamental to physical activitiesgenerally, may have elevated value as to some constituents of anyparticular physical activity. As to such constituents, superior motorcoordination may deliver superior performance not only as to suchelement, but also as to the physical activity overall. As examples,motor coordination may have elevated value as to swinging any athleticequipment, including, e.g., baseball bats, tennis racquets, hockeysticks, lacrosse sticks, and any of the variety of golf clubs. Asfurther examples, motor coordination may have elevated value inlaunching any athletic equipment, including, e.g., pitching a baseball,throwing a football, shooting a basketball, kicking a soccer ball,spiking a volleyball, putting a shot, or throwing a javelin. As furtherexamples, motor coordination may have elevated value in delivering,throwing or otherwise performing any of, e.g., a dive, a vault, atumble, a dance spin, a roundhouse kick or a punch. It is understoodthat, herein, the terms “feedback test”, “performance test” or “test”,or variants thereof, may refer to anything relating to participantfeedback (including, e.g., feedback as to motor coordination, whethergenerally or as to any one or more characteristics), such as, asexamples, the acquisition of imaging (as set forth herein), the analysisof such imaging, and/or the generation/provision of such feedback) Inexample is understood that, herein: (i) the term “physical activity”contemplates any physical activity involving motor coordination,including, without limitation, any of sports and other activitiesreferenced above or otherwise herein; (ii) the term “constituent”contemplates any portion, part, element or other constituent movement ormovements of any such physical activity; and (iii) although anyparticular description herein may reference any one constituent or anyone physical activity, such description is only for purposes ofexplication, simplicity or example, and not to limit the descriptionshereof to such constituent or activity, such that, for example, if theterms “swing” or “swinging” are used herein, those terms are used notonly to describe all swinging-type constituents (regardless of the anyequipment the user swing or swings from), but also all non-swingingmovement/movements, including, without limitation, all of the foregoingnon-swinging constituents.

In example embodiments, a constituent may contemplate component(s) andan activity space. An activity space manifests the physical contextassociated with a physical activity including one or more constituentsthereof, such physical context generally comprising test elements. Anactivity space may be variously implemented, including, e.g., one ormore test elements (such as, boundaries, area(s), equipment, and thelike). A component may contemplate any of, e.g., participant's bodyposition, an participant's body orientation, movement of one or morebody parts, or other action involving the participant, or an absence orsubstantial absence of any of same; or a change as to any of same; or achange of state of a test element (e.g., equipment changing state, suchas being swung, released and/or landing) as relates to the participant'sperformance of the activity or one or more constituents. A componentcontemplating an participant's body position or orientation maycomprise, as to the participant's body or body parts, relativepositioning or orientation among two or more body parts, or positioningor orientation of the body or body part(s) relative to one or more testelements, or combinations of same.

FIGS. 9A and 9B show example activity spaces comprising illustrativetest elements. With reference to FIG. 9A, activity space 900 illustratesexample test elements. Activity space 900 is associated with anArrowhead Agility performance test, which test may be various configuredwith respect to test elements. As to test elements, activity space 900may include area 902, equipment 906A-F, and a start-finish line 908(referred to sometimes herein by the term “start-stop line”). The area902 may have a boundary 904, which boundary may or may not be defined,demarcated or otherwise observable/known by the participant (hereinafter, the terms “participant”, “athlete”, “user” and the like may beemployed and, unless a specific use states or implicates otherwise, theterms are used to refer to the person as to whom imaging ofconstituent(s) is being acquired for the purposes set forth herein).Within area 902, the equipment 906A-F may be positioned at prescribedlocations, which equipment may thereby indicate to the athlete variouslocations for changes in direction or activities in performing the test.The equipment 906A-F may indicate to the athlete the start-stop line908. In an example, the equipment 906A-F includes markers, such ascones, arranged in a predetermined formation: (i) four cones 906A, B, C,E are positioned to form a square with ten-meter sides; (ii) a cone 906Fis centered on the line between cones 906C and 906E; and (iii) cone 906Dis positioned on a line perpendicular to the line formed by cones 906C,906F and 906E, at a distance, e.g., five meters, from 906F, distallyfrom cones 906A, B. The area 902 may be established in, e.g., a portionof a yard, a field, a park, a sporting field, a parking lot, or anyother area that adequately supports the athlete's proper performance ofthe performance test. In this example, area 902 is anticipated to be alevel, firm, non-slippery surface, etc. or at least substantially so(e.g., absent ridges, raised obstacles, holes, bog, mud, slick areas,etc.). In example embodiments, activity space 900 may exclude any one ormore of the foregoing, including all of the foregoing, or may includeany one or more of the foregoing in combination with one or morealternative or additional test elements.

With further reference to FIG. 9A, the activity space 900 may includevarious test elements other than those described above. In exampleembodiments, test elements may include one or more of the following,e.g.: (i) the athlete starts on or behind the start-stop line 908 (e.g.,all points of the stance are on or behind, but not over, the start-stopline 908); (ii) no cone may be touched or otherwise disturbed at anytime; (iii) on the respective run from the start-stop line 908, cones906F, 906E, and 906D are to be rounded, in that order, in the directionsshown in FIG. 9A, with each cone not being stepped over; (iv) on therespective run from the start-stop line 908, cones 906F, 906D, and 906Dare to be rounded, in that order, in the directions shown, with eachcone not being stepped over; (v) on the respective runs from cone 906Dtoward the start-finish line 908, the run is between either cones 906Fand 906E, or cones 906F and 906C, as shown in FIG. 9A; (vi) apredetermined number of repetitions are performed (e.g., fourrepetitions, with 2 in each direction); and/or (vii) between eachrepetition, a predetermined latency (‘recovery interval’) is employed(e.g., a max of 5 minutes between each repetition, with or without aminimum recovery period). In example embodiments, test elements mayexclude any one or more of the foregoing, including all of theforegoing, or may include any one or more of the foregoing incombination with one or more alternative or additional test elements.

In various implementations, an activity may contemplate variousconstituents, and each constituent may contemplate various componentsperformed in an activity space. In an example, wherein the activity isan Arrowhead Agility exercise, constituents or components may includeone or more of the following, e.g.: (i) the athlete assumes aprescribed, initial position (e.g., four-point sprinter's stance,three-point football stance, two-point runner's stance); (ii) theathlete, in stance, remains motionlessness or substantiallymotionlessness (e.g., no rocking, forward lean or counter-movement) fora prescribed time prior to activity or constituent start (e.g., 1 ormore seconds, or such other time, and in any case so as to support thepurposes hereof and, in some examples described herein, in imageprocessing); (iii) the athlete's first movement or substantial movementdefines test start (e.g., movement of a particular body part, ormovement of plural body parts, or relative movement among plural bodyparts, or aggregate body movement); (iv) the athlete's time from thestart-stop line 908 to initiation of rounding of cone 906F; (v) whilerounding cone 906F, relative positioning or orientation among two ormore body parts, or positioning or orientation of the body or bodypart(s) relative to cone 906F and/or the ground, or combinations of same(e.g., seeking maxima or minima, or other statistical indicia respectingthe component); (vi) athlete's time from cone 906F to cone 906E (e.g.,the time from completing the rounding of cone 906F to initiation ofrounding of cone 906E); (vii) while rounding cone 906E, relativepositioning or orientation among two or more body parts, or positioningor orientation of the body or body part(s) relative to cone 906E and/orthe ground, or combinations of same (e.g., seeking maxima or minima, orother statistical indicia respecting the component); (viii) athlete'stime from cone 906E to cone 906D (e.g., the time from completing therounding of cone 906E to initiation of rounding of cone 906D); (ix)while rounding cone 906D, relative positioning or orientation among twoor more body parts, or positioning or orientation of the body or bodypart(s) relative to cone 906D and/or the ground, or combinations of same(e.g., prescribing maxima or minima, or other statistical indiciarespecting the component); (x) athlete's time from cone 906D tostart-stop line 908 (e.g., the time from completing the rounding of cone906D to reaching start-stop line 908); and/or (xi) test completion beingwhen the athlete has crossed the start-stop line 908 (e.g., suchcrossing may be when any body part, specific body part(s) or the entirebody has intersected such line, or has wholly passed beyond such line inthe direction distal from cone 906D). (As per the above, anyintermediate or interposed point between test start and test completionmay sometimes be referred to herein as “test milestone”.) In exampleembodiments of an Arrowhead Agility exercise, constituent and/orcomponents may exclude any one or more of the foregoing, including allof the foregoing, or may include any one or more of the foregoing incombination with one or more alternative or additionalconstituents/components.

As to the example Arrowhead Agility exercise, test results (as describedbelow) may be assessed from the total elapsed time from test start (seeabove re: first movement associated with the athlete's initiation of theperformance test) to test completion (see above re: crossing thestart-stop line 908). Other test results may or may not be assessed fromone or more of the other listed, or of alternative or additional,constituents and/or components, alone or in any combination.

Further referencing FIGS. 9A and 9B, activity space 910 illustratesother example test elements. Activity space 910 is associated with akneeling power ball chest launch exercise, which exercise may bevariously configured with respect to test elements. As to test elements,activity space 910 may include an area 912, equipment 916A-E, and alaunch line 918. The equipment 916B may be a power ball (e.g., a fitnessball, such as a medicine ball, of prescribed weight). The equipment 916Amay indicate to the athlete the launch line 918. Moreover, in exampleembodiments, the equipment 916A may include a pad, rug, or othersurface, which may be planar or flex to the surface beneath, on whichthe athlete may kneel (e.g., comfortably) to perform the test, i.e. tolaunch the power ball 916B. The area 912 may have a boundary 914, whichboundary is shown in the example embodiment of FIG. 9A as generallydemarcated, but which boundary in other example embodiments may or maynot be defined, demarcated or otherwise observable/known by the athlete.As shown, within the area 912, the boundary is generally demarcated byequipment 916A and 916C-E positioned at prescribed locations, wherebythe equipment indicates the boundary 914 wherein the ball may be thrownin performing the test. The equipment 916C-E may include cones placed atprescribed distance(s) from the equipment 916A and/or launch line 918(e.g., the distances may be one or more radial distances so that theequipment 916A, 916C and 916E describe an angle, which angle may bebisected by the line formed between equipment 916A and equipment 916D).The area 912 may be established in, e.g., a portion of a yard, a field,park, a sporting field, a parking lot, or any other area that adequatelysupports the athlete's proper performance of the performance test. Inexample embodiments, activity space 910 may exclude any one or more ofthe foregoing, including all of the foregoing, or may include any one ormore of the foregoing in combination with one or more alternative oradditional test elements.

With further reference to FIG. 9A, the activity space 910 may includevarious test elements other than those described above. In exampleembodiments, test elements may include one or more of the following,e.g.: (i) in an initial, kneeling position, the athlete's knees may beon, or behind, but not over the launch line 918; (ii) so kneeling, theathlete's knees are to be parallel, and the athlete's feet are to beplantar flexed, i.e., pointed away from the launch direction, with thetoes flush to ground, pointed or substantially pointed (e.g., the toesmay not be curled so as to provide additional bracing force to theground); (iii) the ball is to be grasped with both hands, the handsbeing aligned with a diameter of the ball and being positioned onopposite sides of the ball; (iv) the knees are to remain in contact withthe ground or kneepad until at least the release of the ball (e.g., thecomplete release of the ball, such that no portion of the ball remainsin contact with any part of the athlete's body); (v) the ball 916B is toland within boundary 914; and (vii) the athlete's body or portions ofthe body may not cross the launch line until the ball is fully released.In example embodiments, test elements may exclude any one or more of theforegoing, including all of the foregoing, or may include any one ormore of the foregoing in combination with one or more alternative oradditional test elements.

With reference to FIGS. 9A and 9B, a kneeling power ball chest launchexercise may contemplate various constituents and/or componentsperformed in activity space 910. For example, constituents or componentsmay include one or more of the following, e.g.: (i) the athlete assumesa prescribed, initial position (e.g., kneeling, with the back erect andfacing toward equipment 916C-E), while holding the arms (including theball 916B) out and above the head); (ii) the athlete, in the initial,kneeling position, remains motionless or substantially motionless (e.g.,no rocking or similar movement) for a prescribed time prior to teststart (e.g., 1 or more seconds, or such other time, and in any case soas to support the purposes of motionlessness in athleticism rating and,in some examples described herein, in image processing); (iii) theathlete's first movement or substantial movement (e.g., the ball beingbrought down to the chest as the hips are brought back to the heels);(iv) the athlete's movement of a particular body part, or movement ofplural body parts, or relative movement among plural body parts, oraggregate body movement, relating to the translating the ball forwardand up toward the release point; (v) the athlete launches the ball viaboth hands, without favoring one arm, without a throwing rotation ofeither arm and without rotation about the spine; (vi) test start, i.e.,the athlete's release of the ball; and, (vii) test completion, i.e., theball landing, e.g., at a landing point 920 at a distance 922 from thelaunch line 918, in a direction toward equipment 916C-E. In exampleembodiments of a kneeling power ball chest launch exercise, constituentsand/or components may exclude any one or more of the foregoing,including all of the foregoing, or may include any one or more of theforegoing in combination with one or more alternative or additionalconstituents/components.

As to the kneeling power ball chest launch exercise, test results (asdescribed below) may be assessed, e.g., as the distance between thelaunch line 918 (e.g., the edge in the direction of the equipment916C-E) and the landing point 920 (e.g., the central point of the wherethe ball first lands). Such test results may be obtained from theelapsed time between the release of the ball and the ball landing.Additionally or alternatively, such test results may be obtained by acomputation following from the flight time from release to landing.Other test results may or may not be assessed from one or more of otherlisted, or alternative or additional, constituents and/or components,alone or in any combination.

Some test elements associated with activity spaces 900 and/or 910 areshown in FIG. 9A, while others are not. Additional test elements mayinclude ambient conditions, such as, e.g., wind speed and direction,ground condition, rain or other precipitation, temperature, humidity,and the like. Violations of one or more of these conditions may or maynot void the test. In example embodiments, the conditions may beemployed to annotate the test results. As another example, theconditions may be factored into the performance test, including, e.g.,to adjust the test results for comparison or to modify the scoring orrating employing non-adjusted test results.

In example embodiments, the athlete's performance of performance test(s)is measured and/or otherwise converted into representative data (herein,such measurement and/or conversion is sometimes referred to by the term“measurement”, as well as its derivatives thereof; and, suchrepresentative data sometimes is referred to by the term “testresults”). In example embodiments, measurements may include dimensionalmetrics, such as, e.g., time (e.g., elapsed time, of a run, jump oragility test, or of a thrown ball's flight), distance (e.g., distance ofan object's flight), angle (e.g., angle of change in direction), and/orposition (e.g., one body part relative to another or relative to areference, such as the ground or an obstacle). In example embodiments,measurements may include non-dimensional metrics, such as, e.g., counts.Such non-dimensional metrics may be applied to, e.g.: (i) repetitions,e.g., a count of executions of constituent(s) and/or component(s) in aperformance test (for example, total number of push-ups executed in afixed time, whether the execution is proper or not); and/or (ii) fouls,e.g., a count of errors in a performance test (for example, total numberof push-ups in which the athlete bounced their chest off the ground).

Fouls and any associated foul metrics may be implemented variouslywithin a performance test. Implemented “fouls” may be associated, e.g.,with the athlete's improper execution of one or more components orconstituents and/or with the athlete's improper departure from anactivity space. An athlete's improper execution of a component orconstituent may include, as examples: crossing of legs/feet during ashuffle movement (e.g., wherein a proper shuffle contemplates movementvia legs/feet repeatedly being separated and then brought together,without crossing); failing to reach or exceed a threshold angle amongbody parts (e.g., a knee bend in a lunge or a squat); and/or tumbling orother gross loss of body control. An athlete's improper departure froman activity space may include, as examples: moving or being outside anyarea or boundary inside which a performance test is to be performed(e.g., in the kneeling launch test, throwing the ball outside theboundary 914); disturbing a test element (e.g., upending a cone in anagility course); failing to interact properly with a test element (e.g.,failing to touch a cone when such touch is a test element; or touching acone when not touching is a test element; or failing to round a cone orto stay to the inside or outside of a cone; etc.); failing to abide atest element (e.g., failing to maintain prescribed time conditions, suchas motionlessness for a set time, or executing a repetition after alatency period and/or recovery interval has expired); and/or improperlyexploiting a test element (e.g., pushing or pulling on a course markeras impetus for a test's change-of-direction, or bouncing one's chest offthe ground as impetus for the upward movement in a push-up).

In example embodiments, foul(s) and any associated metric(s) may beconsequential. Consequences may be variously implemented, including,e.g.: (a) disqualification (aka rejection) of a test result (such asresponsive to, e.g., any of: a false start, a running start, an improperball grasp during or rocking movement in a kneeling power ball chestlaunch test, assuming a position that delivers an unfair advantage in atest; a foul exceeding a predetermined threshold; any/or an aggregatefoul count exceeding a predetermined threshold); (b) adding apredetermined time quantum to a test result measured via of time metric,e.g., such time quantum being responsive to the time benefit accrued dueto the improper movement, possibly together with a penalty (e.g., 0.02seconds for each upended cone, wherein the benefit to the athlete's timeis predetermined to be 0.01 seconds for each such upended cone andwherein 0.01 seconds is assessed as a penalty); or (c) subtracting apredetermined distance quantum to a test result measured via of distancemetric, e.g., such distance quantum being responsive to the benefitaccrued due to the improper movement, possibly together with a penalty.In example embodiments, the resultant test results are the test resultsfrom measurement, as subjected to any adjustment (e.g., viadisqualification, addition, subtraction or otherwise).

In example embodiments, only consequential fouls are detected, measuredand acted on, such as being reported as to, treated or otherwiseincluded in or with, test results. In example embodiments, consequentialfouls may be acted on by negating test results. In example embodiments,non-consequential fouls may be detected (alone or together withconsequential fouls), which detection may be acted on, e.g., forcoaching or other direction, such as to instruct the athlete towardaddressing such fouls and, thereby, enabling improvement of testresults.

In example embodiments, the athlete may be enabled to obtain image datatoward proving participant feedback as described herein, e.g., via useof one or more portable electronic device(s) 924A, 924B, which device(s)support capabilities further described herein, which capabilitiesinclude, but are not limited to, image acquisition capabilities,particularly acquisition of a sequence of images (e.g., such sequence ofimages including video frames and/or still images) with acquisitionparameters so as to enable sufficient image data for image processing toyield outputs that, in turn, enable provision of, e.g., participantfeedback. In example embodiments, such portable electronic device(s) mayinclude a general purpose device, such as a smart phone (e.g., the HTCOne X+) or may be a special purpose device (e.g., integratingcapabilities specifically to provide a system and/or method inaccordance with the descriptions herein). In example embodiments, eachsuch device's image acquisition capabilities are used to acquire imagesof an activity, including as to one or more constituents, as well ascomponents thereof. As shown in FIG. 9A, a portable electronic device924A/B may be arranged by or for the athlete in association with therespective activity space 900, 910. So arranged, the portable electronicdevice 924A/B may be enabled to acquire images of the athlete's conductas to the activity.

A device 924 may be arranged to enable such image acquisition in variousmanners, including, e.g., by a mount or by being hand held. As shown inFIG. 9A, the athlete may arrange a portable electronic device 924B sothat it is held by a second person (e.g., a friend, teammate or anotherathlete also self-directing their own performance tests, etc.). As alsoshown in FIG. 9A, the athlete may arrange a portable device 924A via amount on a tripod 926, whereby the mount enables the device's field ofview 934A for image acquisition to be directed so as to cover therespective performance test. Alternatively, and provided such imageacquisition is enabled, the athlete may otherwise arrange a device 924via other mounts or other fixed devices (herein referred to collectivelyby the term “mount” and its derivatives), including via, e.g.: (i)placement directly on turf or ground (e.g., if the activity space is anoutdoor field, such as a playing field); (ii) placement directly on acourt (e.g., if the activity space is a basketball, volleyball or otherindoor court); (iii) insertion in a bag pocket; or (iv) mounting on anitem located in association with the activity space (e.g., a tree, abasketball post, a football post, a lamp post, a wall, etc.).Alternatively, another individual 928, which may be a trainer, coach,friend, colleague or other person, may hold and/or operate the portabledevice 924.

Among these arrangements, a device 924 may be provided with lesser orgreater stability. When arranged via a tripod 926, a device 924typically is provided with substantial stability. When arranged via amount other than a tripod 926, a device 924 typically is yet providedwith a level of enhanced stability, at least as compared to a hand-heldarrangement. By contrast, when in a hand-held arrangement, a device 924may be provided with less stability, or inconsistent stability, ascompared to a mounted arrangement.

When stably arranged, e.g., via a tripod 926, a device 924 tends not tomove, or not to move substantially, during image acquisition of aperformance test. That stable arrangement typically enables imageacquisition without, or with insubstantial, impact as to the acquiredimages and associated image data. A less stable arrangement—or anarrangement providing stability below a minimum threshold (e.g., underambient conditions)—tends to subject acquired images and associatedimage data to a non-insubstantial impact. Such impact may include, e.g.,aberrant motion of objects in the imaging. As an example, the device'sphysical movement may cause an object to appear to have motion among theimages, notwithstanding that the object's corresponding physical itemmay have been stationary during the images' acquisition. As anotherexample, if an object's corresponding physical item were to haveactually been moving during the images' acquisition, the object mayappear to have motion that is greater or lesser than the correspondingitem's actual, physical movement. With aberrant motion of objects causedby the device's physical movement (e.g., physical movement of thedevice's imaging acquisitions capabilities, particularly the imagingchip), all objects of the images are impacted. Accordingly, in exampleembodiments, systems and methods contemplate employ of image processingtechnologies for detecting, estimating and otherwise addressing suchaberrant motion, which technologies may be selected not only forcapabilities re such addressing role, but also for compatibility withthe image-based measurements as to performance tests as contemplatedherein and, thus, to support provision of participant feedback.

As previously described with reference to FIG. 9A, a portable electronicdevice 924A, 924B may be arranged so that the device may be enabled toacquire images as to a performance test. In example embodiments, inacquiring images, a portable electronic device is not only arranged toenable image acquisition generally, but also positioned to provideproper image acquisition (i.e., image acquisition enabling imageprocessing technologies to yield outputs enabling image-basedmeasurements as to performance tests). Such positioning may respond tovarious factors, including, e.g., (i) the applicable test's activityspace (e.g., physical dimensions) and (ii) the focal length, apertureand quality of the device's imaging lens, as well as theformat/resolution applicable to the imaging. Generally, the lens' focallength is indicative of (i.e., inversely proportional to) the device'sfield of view 934A, B, while the focal length/aperture are indicative ofthe depth of field. The imaging's format/resolution is indicative of theamount of image data.

As an example with reference to FIG. 9A, a portable electronic device924A may be positioned so that the device's field of view 934A enablesimage acquisition of the athlete as the athlete conducts the ArrowheadAgility exercise. In such positioning, the field of view 934A covers theentirety of the activity space 900, so as to enable imaging of all ofthe athlete's activities throughout the test. However, in order to coverthat entirety within the field of view 934A, the device 924 may bepositioned at a distance from the activity space 900 which distance hasthe activity space 900 toward, or even effectively in, the imaging'sbackground 930. As well, the device 924 may be positioned at a distancewhich has the activity space 900 partly in the imaging's background 930and partly in the imaging's foreground 932. In either case, one or moreobjects (such as, the object that corresponds to the athlete) may beinsufficiently imaged, such that insufficient image data is availablefor image processing technologies to yield outputs enabling image-basedmeasurements as to constituents and/or components and, thus, to supportprovision of participant feedback. In example embodiments, systems andmethods contemplate employ of image processing technologies fordetecting improper positioning, including, e.g., to notify the athleteto re-position.

As shown in FIG. 9A, a portable electronic device 924A, 924B may beproperly positioned whether or not the field of view 934A, 934B coversthe entirety of the performance test. As an example, as shown in FIG.9A, the device 924A may be properly positioned and have its field ofview 934A covering the entirety of the activity space 900 as to thearrowhead agility performance test. However, the device 924A, sopositioned, has its field of view 934A not covering the entirety of theactivity space 910 shown in FIG. 9A, which space 910 is associated withthe kneeling power ball chest launch performance test. As to at leastthe portion of the activity space 910 that is not covered by the fieldof view 934A, a second portable electronic device 924B, via its field ofview 934B, may be employed in order to provide entire coverage of thekneeling power ball chest launch performance test. Accordingly, inexample embodiments, systems and methods may contemplate employment ofcommunication/control technologies and/or image processing technologies,so as to variously coordinate plural portable electronic devices 924(e.g., calibration, shutter synchronization and/or offsets) and processamong such devices' plural sequences of acquired images (e.g., mosaicprocessing).

In example embodiments, a portable electronic device 924A, 924B includesimage acquisition capabilities. In example embodiments, a portableelectronic device 924A, 924B includes not only image acquisitioncapabilities, but also other capabilities, including, e.g., one or moreof: (i) processing capabilities; (ii) communication capabilities (e.g.,supporting wireless communications for communications/control amongportable electronic devices 924, as well as with other sensor,electronic or computer devices); (iii) networking capabilities (e.g.,for communications in any one or more networks, such as body areanetworks (BAN), personal area networks (PAN), local area networks (LAN)and wide area networks (WAN)); (iv) data acquisition capabilities (e.g.,via one or more sensors internal or external to the device 924, such asone or more accelerometer(s), gyroscope(s), compass(es), othermagnetometers, barometer(s), other pressure sensor(s), thermometer(s),other temperature sensor(s), microphone(s), other sonic sensor(s) (e.g.,ultra-sonic sensor(s)), infrared (iR) sensor(s), and/or otherelectromagnetic radiation sensor(s)); (v) input/control capabilities(e.g., including via physical buttons, logical buttons enabled via atouch screen, voice input controls, and/or other input controls); (vi)output/notification capabilities (e.g., via LED light(s), a display, atouch-sensitive display, speaker(s), other audio transducer); and/or(vii) location detection capabilities (e.g., for identifying location(s)relative to other devices 924, or relative to sensors, equipment, ordevices, or relative to test elements or the activity space, such as byGPS, AGPS signal analysis, signal strength measurements, or othertechnologies, including via data acquired from sensors, transceivers orother electronic devices embedded in equipment, apparel, footwear and/oraccessories, and/or in other device(s) 924, including in combination(s),and/or in combination(s) with other devices 924).

In example embodiments that include processing capabilities, suchprocessing capabilities may be implemented so as to execute, or cause tobe executed, one or more sets of software instructions, including, e.g.,mobile software application(s) and/or embedded applications, and/oroperating system(s). Such processing capabilities, executing one or moresuch software instruction set(s) may be implemented to control suchimage acquisition capabilities, in whole or in part (such softwareinstruction set(s) herein sometimes referred to by the term “imageacquisition software”). Such processing capabilities and imageacquisition software, either alone or together, may enable, one or moreof, as examples: acquisition of one or more sequences of images (e.g.,sequences of still images and/or video frames, which sequences of imagesand/or frames are herein sometimes referred to by the term “images” or“imaging”); control of the start and stop of each such sequence(including, e.g., coordinating among plural devices' imaging acquisitioncapabilities); control of any latency applicable to any sequence (e.g.,delay between sequences and/or time offset for starting acquisition,such as against a reference or among plural devices' image acquisitioncapabilities); control of the acquisition frequency (e.g., frames orimages acquired per unit time); control of the resolution and/orformatting applicable to the imaging (e.g., total pixels per image orframe, and/or the number of lines per image or frame and the number ofpixels per line); control of any pre-processing of acquired image data(e.g., imager noise reduction, contrast control, etc.); and/or, controlor selection of other imaging parameters.

In embodiments that include processing capabilities, such processingcapabilities may be implemented so as to execute, or cause to beexecuted, one or more sets of computer-executable instructions on one ormore non-transitory computer-readable mediums implementing one or moreimage processing technologies (such example instruction set(s) hereinsometimes referred to by the term “image processing software”). Inexample embodiments, such image processing software includes imageprocessing technologies directed to processing, analyzing, and otherwiseextracting information from the one or more sequences of images acquiredwith respect to one or more constituents and/or components. In exampleembodiments, such image processing software may implement one or moretechnologies, including, e.g., any of various technologies of orrelating to computer vision. In example embodiments, such imageprocessing software may implement one or more image processingtechnologies sometimes referenced, sometimes among other terms, as:sequential frame analysis; sequential image analysis; image sequenceanalysis; video sequence analysis; stixel motion analysis, optical flowanalysis; motion vector analysis; frame motion analysis; motionestimation; feature-based motion estimation; motion detection; changedetection; frame differencing; sequential image differencing;segmentation; feature (based) segmentation; object segmentation; colorsegmentation; intensity segmentation; motion (based) segmentation;change detection segmentation; feature extraction; object recognition;pattern recognition; pattern matching; position estimation; backgroundsubtraction; image filtering; and global motion detection/removal (e.g.,toward negating ego-motion). It is understood that the foregoingtechnologies list is not exhaustive. It is understood that the foregoingtechnologies list may include one or more generic among respectivespecies, and/or components of either. It is understood that theforegoing technologies list may include one or more terms for the same,or substantially the same, or overlapping, technologies. It isunderstood that, in any employed image processing software, output(s) ofany first of such listed technologies may be input(s) for such first orone or more second listed technology and, in turn, output(s) from suchsecond listed technology or technologies may be input(s) for such secondlisted technologies or such first listed technology, in one or moreiterations/recursions/updates. It is also understood that such software,supporting such technologies, may be configured to employ a prioriknowledge of the performance test (e.g., test elements (e.g., the typeof golf club), constituents, components, athlete height and/or otherathlete characteristics, anticipated test duration(s), etc.) so as toenhance both acquisition of imaging sequences (e.g., via sufficientlyearly start, and sufficiently late termination, of acquisition relativeto the conduct of the activity, constituent and/or component) andanalysis of imaging as described herein (e.g., to advancesegmentation/detection/motion estimation among objects, including inphases among objects and sub-objects, such as, in a first phase,analysis as to general movement, such as of the athlete's body and, in asecond phase, analysis of specific or relative movement of/among theathlete's body, head, torso, arms, legs, equipment etc.). It is alsounderstood that any image processing technologies generally provides forprocessing of (i) still images (individually or as some set orsequence), (ii) video or videos (e.g., plural video clips, such clipshaving a known relationship there among in re a performance test);and/or (iii) any combination of still image(s), video, and/or videos.(Any such processing, such as via any such image processingtechnologies, may sometimes be referred to herein by the term “imageprocessing”.)

In example embodiments, such processing capabilities executing imageprocessing software may be implemented so as to process, or cause to beprocessed (e.g., via the device's one or more operating system(s) orembedded software instruction sets), one or more sequences of imagesacquired with respect to one or more performance tests toward yieldingoutputs for enabling provision of participant feedback, e.g., for one ormore constituents and/or components. In various example embodiments,processing capabilities executing image processing software may beimplemented so as to process, or cause to be processed (e.g., via thedevice's one or more operating system(s) or embedded softwareinstruction sets), one or more sequences of images acquired with respectto one or more constituents and/or components, wherein such processingmay be directed to one or more of the following operations, e.g.: (i)identifying images associated with the athlete's selected constituent(s)and/or component(s) described herein; (ii) detecting, confirming and/ormonitoring test elements, via imaging (e.g., confirming arrangement ofcones at proper locations and separations; confirming proper areaproperties, such as levelness and absence of obstacles, ambientconditions, etc.); (iii) identifying, detecting, confirming and/ormonitoring components, via imaging (e.g., confirming the athlete assumesa prescribed, initial position and, in the initial position, the athleteremains motionlessness or substantially motionlessness for a prescribedtime prior to test start; confirming athlete form, such as via relativepositioning or orientation among two or more body parts before, at teststart, or during conduct of, a test; confirming relative positioning ororientation of the athlete's body or specified body part(s) relative toa test element before, at test start, or during conduct of, a test);(iv) detecting, measuring and acting on fouls (e.g., detectingconsequential and/or non-consequential fouls), as described herein; (v)detecting, estimating and otherwise addressing aberrant motion ofimaging objects (e.g., aberrant motion caused by physical movement ofthe portable electronic device's image acquisition capabilities); and/or(v) detecting improper positioning of the portable electronic device924A, 924B in the employ of its image acquisition capabilitiesrespecting a constituent or component. It is understood that, in someexample embodiments, processing capabilities executing image processingsoftware may be implemented so as to exclude any one or more of theforegoing operations, including all of the foregoing operations, or mayinclude any one or more of the foregoing operations in combination withone or more alternative or additional operations.

In embodiments that include processing capabilities, such processingcapabilities may be implemented so as to execute, or cause to beexecuted, one or more sets of computer-executable instructions on one ormore non-transitory computer-readable mediums implementing one or morefeedback processing technologies (such instruction set(s) hereinsometimes referred to by the term “feedback processing software”). Suchprocessing capabilities, executing such feedback processing software,may be implemented to provide, from the outputs of the image processingsoftware, either/both test results for one or more such performancetests and/or feedback as to one or more constituents and/or components,as described herein. In example embodiments, based on the imageprocessing software detecting images associated, respectively with teststart and test completion in the conduct of a performance test, thefeedback processing software may be implemented to identify the numberof images from the test start to the test completion and, based on theacquisition frequency, calculate test results for such conduct as anelapsed time. In example embodiments, based on the image processingsoftware detecting images associated, respectively with test milestonesarising in the conduct of a performance test, the feedback processingsoftware may be implemented to identify the number of images from thetest start to one or more selected test milestones, from any selectedtest milestone to any other selected test milestones, and/or from anyone or more selected test milestones to the test completion; and, basedon the acquisition frequency, calculate test results for such conduct asan elapsed time. In example embodiments, based on the image processingsoftware detecting images associated, respectively with test milestonesarising in the conduct of a performance test, the feedback processingsoftware may be implemented to process images associated with any testmilestone, or among selected test milestones, or among any selected testmilestone and test start and/or test completion, such image processingbeing directed, e.g., to identify issues of form, or to identifyopportunities to improve performance, or to otherwise enhanceperformance, such as for coaching, whether for self-coaching or forassistance from a coach, trainer or otherwise. In example embodiments,based on the image processing software detecting images associated,respectively a constituent (including one or more of its components) inthe conduct of a performance test, the feedback processing software maybe implemented to process such images, e.g., toward providingparticipant feedback, or toward identifying issues of form, or toidentify opportunities to improve performance, or to enhance performancevia coaching, whether for self-coaching or for assistance from a coach,trainer or otherwise. Such image processing and analysis as to form,e.g., may be directed to identifying, confirming, assessing or otherwiseanalyzing, as to the athlete's body or body parts, relative positioningor orientation among two or more body parts, or positioning ororientation of the body or body part(s) relative to one or more testelements, e.g., in or among test milestones, test start and/or testcompletion.

It is understood that, in one or more of the example embodimentsdescribed herein that employ a portable electronic device 924, suchexample embodiments may be implemented to employ, additionally oralternatively, device(s) other than a portable electronic device 924. Itis also understood that, as to one or more of the example embodimentsdescribed herein, a portable device 924 may be implemented via generalpurpose architecture (i.e., hardware, software, etc. toward supportingoperations different from, in additional to, or potentially in theabsence of the imaging-directed operations described herein), or via anapplication specific architecture (i.e., hardware, software, etc. towardsupporting only the operations described herein), or via anotherapproach so that the device enables the operations described herein bymeans of some combination with one or more other devices. It is alsounderstood that, as to one or more of the example embodiments describingprocessing herein, such processing may be variously executed, including,as examples: (i) via a portable electronic device 924 (e.g., via suchdevice's internal processing capabilities); (ii) among portableelectronic devices 924 (e.g., via communications and/or networkingcapabilities); (iii) among one or more portable electronic devices 924in combination with one or more processing capabilities external to anysuch device 924; (iv) via processing capabilities external to any suchdevice 924 (e.g., processing capabilities provided in association withone or more sensors, or by means of an athlete's device other thandevice 924, or through one or more remote processing center(s), or viacloud services), any one or more of which may be accessed via, a.o., anathlete's BAN, PAN, LAN or WAN; or (iv) at any time and over time, byany one of these, or among any combination of these (e.g., as arbitratedrespecting and otherwise responsive to, a.o., processing volume, timeconstraints, competing processing constraints/priorities, power/energydemands/capacities, processing power, etc.).

Referring to FIG. 10, an exemplary method 1000 is illustrated forgenerating an feedback and/or test results, via imaging. At step 1002,labeled “Start”, the method may be initiated. As an example, the methodmay be initiated by, e.g., an athlete electing to conduct a performancetest. As another example, the method may be initiated iteratively,including, as examples: (i) if the athlete elects to conduct, in series,a battery of performance tests; (ii) as to any performance test, pluraliterations of the test are prescribed; (iii) from images acquired duringconduct of any performance test, image processing detects a foul, orother circumstances that negates the test and motivates starting anew;and/or (iv) an improper condition is detected (e.g., a tail wind when asprinting performance test is anticipated), so as to motivate startinganew. In example embodiments, the athlete may so elect with or withoutemploying any device 924 or otherwise. That is, the athlete may so electby committing to conduct performance tests.

At step 1004, a performance test may be identified. In exampleembodiments, the athlete may identify a performance test without aid ofany device. In other example embodiments, the athlete may employ aportable electronic device 924 (e.g., having a display and executingcomputer-executable instructions on a non-transitory computer-readablemedium (e.g. mobile software application(s)), whereby the identificationmay be via a graphic user interface. Such graphic user interface mayemploy any of various user interface facilities (e.g., menus) to supportidentification, including, as examples, displaying supported tests so asto enable the athlete to select there among, displaying tests (by sport,activity, constituent and/or component), displaying tests as batteries(by sport, activity, constituent and/or component), displaying thecurrent test in a series of tests so as to guide the athlete (e.g.,through a battery of tests), displaying the tests that the athlete haspreviously conducted or indicated interest in conducting, and the like.In example embodiments, in this step 1004, the athlete may reject,select or confirm an activity, constituent and/or component.

At step 1006, the activity space may be set. In example embodiments, theathlete (alone or with assistance) may physically establish, deploy,obtain or otherwise set up the activity space, including as to any oneor more of the test's area, boundary, equipment or other prescribed testelements. In example embodiments, the athlete may be enabled to do sovia use of plural device(s) 924, or via use of the device(s) 924 incombination with, or via employ of, associated mechanisms, whichmechanisms may or may not be electronic in nature. Electronic mechanismsmay include or support ranging and orientation capabilities, includingvia compass, signal strength, laser ranging, or other facilities.Non-electronic mechanisms may include or support ranging and orientationcapabilities via having defined size or markings. As to use ofelectronic mechanisms and/or plural devices 924, the devices 924 andelectronic mechanisms may coordinate to determine distances via signalstrength metering or other ranging there between, and orientation via,e.g., compassing. As to use of the non-electronic mechanisms, thedevices 924 may determine distances and orientations by imaging, i.e.,the ratio of imaged to actual size of the non-electronic mechanism(s) atcandidate location(s), such locations oriented via, e.g., the device'scompass.

At step 1008, portable electronic device(s) 1024 are arranged/positionedfor image acquisition. As described herein, such device(s) may bearranged via various mounts or by being hand-held (e.g., by a personselected by the athlete). In this step, such device(s) may be positionedin association with the area/boundary of the activity space. Suchpositioning may be preliminary, in that the positioning may be adjustedto improve imaging acquisition (e.g., toward positioning the activityspace in the imaging foreground 1032, as described herein, includingwith respect to step 1012 below).

At step 1010, as to example embodiments employing a portable electronicdevice 1024 that executes, or causes to be executed, one or more sets ofsoftware instructions, one or more of such instruction set(s) may belaunched. In example embodiments, such instructions set(s) are directedto supporting participant feedback(s), as described herein. In exampleembodiments, at step 1010, launch may be directed to one or more ofimage acquisition software, image processing software, and/or feedbackprocessing software, alone or in combination, including, in combinationwith one or more of, e.g., other mobile software application(s), and/orembedded applications, and/or operating system(s). In exampleembodiments, such image acquisition software, image processing software,and/or feedback processing software may be integrated (e.g., as anfeedback processing “app”).

At step 1010, as to example embodiments employing a portable electronicdevice 1024, such launch may be variously provided. In an exampleembodiment wherein the device 1024 is implemented via general purposearchitecture (e.g., as a smart phone), launch may be provided, e.g., viaan athlete (or assistant) touching an icon on a touch screen display,which icon represents the applicable software. In an example embodimentwherein the device 1024 is implemented via an application specificarchitecture, launch may be provided, e.g., when an athlete (orassistant) powers on the device. In either case, launch via step 1010may be omitted if, at step 1004, the athlete identified the test via thedevice 1024, as described therein.

At step 1012, the field of view is set for image acquisition as to theactivity space. In example embodiments wherein image acquisitioncapabilities are provided via portable electronic device(s) 1024, theathlete may arrange/position portable device(s) 1024 whereby the fieldof view 1034 is directed to cover some or all of the activity spaceassociated with a respective performance test, as described herein.

In so arranging/positioning device(s) 1024 as to field of view, however,device 1024 may be arranged/positioned at a distance from the activityspace 1000 which distance is sufficiently large as to risk one or moreimaged objects (e.g., the imaging sequence's object that corresponds tothe athlete) being insufficiently imaged for proper image processing.Other positioning, arrangement or other physical staging issues may alsoarise, including, as examples: (i) positioning that introduces lightingissues (e.g., sun or other bright light, or shadows or other low light,or other lighting that may impede proper image acquisition); (ii)positioning sufficiently proximate to or in the activity space so as torisk one or more imaged objects not being acquired at all or not fullyacquired (e.g., although detection of the athlete's kneeling is sought,proximate positioning may cause imaging to omit objects corresponding tothe athlete's knees); (iii) arrangement(s) in which camera movement issubstantial, or excessively high (e.g., as to a hand-held imagingdevice, image motions sourced from device movement may be substantiallyor overly difficult to remove or otherwise address); and/or (iv)circumstances implicating excessive or overly confusing motion presentin the sequence of images (e.g., besides the athlete, other activepersons are in the field of view, particularly in the foreground of theactivity space, in sufficient number and/or at sufficient activitylevel(s) as to impede image processing or confidence therein).

Responsive to issues arising from positioning, arrangement or otherwiserelating to physically staging the device with respect to imageacquisition, example embodiments, at step 1012, may implement pre-testimage processing, i.e., toward one or more of: detecting any imagingissues; characterizing the issues; notifying the athlete of the issues;suggesting potential solutions or other means to address the issues;suspending or terminating next steps in operations, including until someor all issue(s) are resolved or sufficiently resolved; iterating any oneor more of these; and/or shutting down. As described herein, in exampleembodiments, the device 924 may suggest re-positioning of the device.

In example embodiments, at step 1012 or other pre-test step, ambientconditions may be detected, analyzed (e.g., against test elements) andacted upon, as described herein. Such ambient conditions may be detectedvia device(s) 924, including via, e.g., (i) sensors, whether suchsensors are internal to device(s) 924 or are external thereto, such asintegrated into the athletes apparel, footwear or accessories orprovided in other devices within the athlete's instant BAN, PAN, or LAN;(ii) data sources, which data sources may be accessible to the device(s)924 based on LAN or WAN (e.g., where device(s) 924 comprise a smartphone, weather service entities may provide current local conditions viacellular or Wi-Fi connectivity, or other software may includefeature(s)/function(s) enabling such data to be obtained. In exampleembodiments, ambient conditions may be analyzed and acted upon by, a.o.possibilities, precluding or voiding a test, or informing a change inthe setup of the activity space (e.g., re-positioning the test elementsso that a sprint is run with wind directed perpendicular to the runninglane).

At decision 1014, example embodiments may implement an “acquisitionready” event test. In such step 1014, if an acquisition ready event isor has been detected, image acquisition will proceed. If such readyevent is not or has not been detected, image acquisition will notproceed. In the latter case, example embodiments may provide for thetest to be repeated until a ready event is detected. Other exampleembodiments may provide for the test to repeated until one or moreconfigured threshold(s) are met or exceeded, e.g., number ofrepetitions, a timer expires (e.g., starting from launch or otherreference), or otherwise. Such other example embodiments may provide for(i) repetition(s) of any of the foregoing steps, or components of theforegoing steps (e.g., identification of a performance test, orconfirmation of a previously identified performance test, or pre-testimage processing, or ambient conditions detection), or (ii) endingoperations, or (iii) having repetitions subject to a first threshold (T1at decision 1016) and re-starting or ending operations subject to asecond such threshold (T2 at decision1018). A re-start may include, asexamples, notification to the athlete via a device's output/notificationcapabilities (e.g., a visible warning signal, such as via a LED light; awarning screen splashed on the display; an audible warning signalsounded by speaker(s), or a combination of these). Alternatively, theprocess may terminate if the threshold is larger than T2 at decision1018.

In example embodiments, an “acquisition ready” event may be variouslyimplemented. As examples, a ready event may be implemented to be, asexamples: (i) properly concluding any of the steps 1004-1012, orcomponents thereof; (ii) properly re-positioning so as to enable imageprocessing; (iii) engaging prescribed input/control capabilities ofdevice(s) 1024 (e.g., pushing a prescribed physical or logical button,or articulating a prescribed voice command as to voice input controls),including via a device 924 that may be retained by the athlete (e.g.,device 112 of FIG. 1); and/or (iv) performing (by the athlete or for theathlete, such as by an assistant) prescribed act(s), such act(s) beingamenable for detection via image acquisition or data acquisitioncapabilities (e.g., exhibiting a prescribed body gesture for receptionvia the image acquisition capabilities, or issuing a prescribed gesturevia sensors embedded in apparel, footwear, and/or accessories).

At step 1022, images may be acquired. As described herein, such imagesmay be acquired variously. In example embodiments, generally, imageacquisition is subject to parameters which may be configured so as toenable, enhance, optimize or otherwise provide for image processing forthe purposes described herein. In example embodiments as describedherein, images may be acquired via one or plural devices 924. As anexample of plural devices 924, two devices are employed, wherein (i)such devices are calibrated for operation together (e.g., via knowncalibration approaches), so that (ii) one device 924 may acquire imagesassociated with test start, and (iii) a second device 924 may acquireimages associated with test completion. As another example employing twodevices 924, both devices 924 may capture test start and/or testcompletion, whereby the images from each may be combined, in whole or inpart, or otherwise, towards obtaining enhanced image processing and,thereby, enhanced assessments of initiation image and/or completionimage (and/or, through shutter offsets, enhanced timing precision) and,in turn, enhanced test results and/or feedback.

At decision 1024, example embodiments may implement an “imagesretention” event test. At decision 1024, if an images retention event isor has been detected, image acquisition operations continue, andoperations flow, e.g., to decision 1026. If such event is not or has notbeen detected, image acquisition operations continue, but exampleembodiments may implement an image discard process 1028.

In example embodiments, an images retention event may be implemented soas to enable acquisition of images in anticipation of upcoming teststart for a performance test, while also providing, e.g., if test startis subject to delay, retention of a reasonable number of images (e.g.,so as to preserve image storage space for relevant images). As anexample, if image acquisition is proceeding, but the athlete has not yetentered the activity space, images retention may not be merited. Asanother example, if image acquisition is proceeding and the athlete hasentered the activity space, but not progressing toward initiation ofperformance test conduct, images retention may not be merited. Asanother example, if images acquisition is proceeding and the athlete hasnot only entered the activity space, but also is progressing towardinitiation of performance test conduct, images retention may be merited.

An images retention event may be variously implemented. In exampleembodiments, an images retention event may be implemented to be or to beassociated with, as examples: (i) the athlete engaging (or havingengaged by an assistant) prescribed input/control capabilities ofdevice(s) 924 (e.g., pushing a prescribed physical or logical button, orarticulating a prescribed voice command as to voice input controls),including via a device 924 that may be retained by the athlete (e.g.,portable device 112 of FIG. 1); (ii) the athlete performing (or havingperformed by an assistant) prescribed act(s), such act(s) being amenablefor detection via image acquisition or data acquisition capabilities(e.g., exhibiting a prescribed body gesture for reception via the imageacquisition capabilities, or issuing a prescribed gesture via sensorsembedded in apparel, footwear, and/or accessories); and/or (iii) theathlete preparing in the activity space to conduct a performance test,which conduct preparation may be amenable to detection by imageacquisition capabilities.

As to conduct preparation as an images retention event, exampleembodiments may be implemented to detect any/selected such events viaimage processing. In configuring image processing for such detection,understood is that the athlete is preparing in the activity space and,as such, that acquired images may be anticipated to include object(s)corresponding to the athlete, and that at least such object(s) mayexhibit motion(s) among images, e.g., from image to image in thesequence. With such understandings, an images retention event may bedeemed to have occurred if, as an example, motion is detected thatsatisfies (e.g., meets, or exceeds) a selected images retentionthreshold. In this example approach, such detection may assess motionacross a selected number of consecutive images in a sequence, or may beapplied as to a selected number of non-consecutive images in a sequence,or otherwise.

As to the prescribed act(s), example embodiments may be implemented inwhich such act(s) include one or more components. As examples, suchact(s) may be an “initial position” (as described hereinabove), or maybe such “initial position” combined with preceding or subsequent athleteactivity. To illustrate, an arrowhead agility exercise, as describedherein, may include various constituents, and each constituent mayinclude various components, such that, among other components serving asor to formulate prescribed act(s), such act may be either/both (i) aprescribed stance as an initial position and (ii) a prescribed period ofmotionlessness or substantial motionlessness in such stance prior totest start. As another illustration, a kneeling power ball chest launchexercise, as described herein, may include various constituents, andeach constituent may include various components, such that, among othercomponents serving as or to formulate prescribed act(s), such act may beeither/both (i) a prescribed, kneeling stance as an initial position and(ii) a prescribed period of motionless or substantially motionless insuch stance prior to test start.

For an images event retention test wherein selected component(s) serveto signal the event, example embodiments are implemented towarddetecting such components and, upon such detection, enabling operationsto proceed. In configuring image processing for such detection,understood is that the athlete is preparing in the activity space and,as such, that acquired images may be anticipated to include object(s)corresponding to the athlete and or equipment, and that at least suchobject(s) may exhibit motions among images, e.g., from image to image inthe sequence. With such understandings and employing image processing,an images retention event may be deemed to have occurred if, as anexample, motion of the sequence is detected to approach or pass aselected threshold (e.g., pass below a low threshold, as such motionvalue may follow from or be associated with the prescribedmotionlessness associated with an “initial position”). Further to theabove, an images retention event may be deemed to have occurred if, asan example, motion in the sequence is detected not only to approach orpass a selected threshold, but also to be sustained at or near, orotherwise within some range thereabout (e.g., for a time period relatingto the prescribed period of athlete motionlessness in the “initialposition”). In this example approach, such detection may be implementedin various ways, including, as examples, to assess motion across aselected number of consecutive images in a sequence, or may be appliedas to a selected number of non-consecutive images in a sequence, orotherwise.

Example embodiments may be implemented to detect an images retentionevent via a combination of foregoing approaches. As an example, imageprocessing may be employed in such embodiments to detect an imagesretention event when the motion of the sequence approaches or passes aselected threshold, including, e.g., with the qualification that suchmotion value is preceded and/or followed by a relatively higher or lowermotion value.

In the foregoing example approaches, such detection may or may not belimited to detection of motion as to object(s) corresponding to theathlete and/or certain equipment (e.g., relevant motion may be thatamong frames as a whole). As such, images retention event detection maybe implemented via image processing at a relatively high level (e.g.,via frame differencing).

Under the circumstance wherein an images retention event is notdetected, example embodiments may include an image discard process,which process may be variously implemented. As examples, an imagediscard process may discard (e.g., from image memory) images as follows:(i) discard all images acquired as of a configured step (e.g., thatdecision 1026 or a prior step, such as, e.g., ready event, at step1014); (ii) discard a configured quantity of images (e.g., via a numberof images, or as to a percentage of the total number of images, withsuch number or percentage being determined via various understandings,estimates or other factors, including, e.g., the acquisition frequencyand typical time periods that may be associated with activitiesprefatory to performance test conduct); or (iii) discard a calculatednumber of images (e.g., based on image memory size, image acquisitiontime, image acquisition frequency, image resolution, number of imagers,estimated imaging durations, safety margins, etc.). In exampleembodiments, an image discard process discards images that precedeimages of potential relevance to an images retention event. In exampleembodiments, an image discard process protects images that arepotentially relevant to detection of an images retention event, e.g., bynot discarding at all, or by preserving in a buffer, e.g., for aconfigured time).

From the images retention event, operations flow to a “confirming” eventtest, at decision 1026. If a confirming event is or has been detected,image acquisition continues, and operations flow, e.g., to decision1034. If such confirming event is not or has not been detected, imageacquisition continues, and operations flow to a standby process, atdecisions 1030, 1032.

In example embodiments, a standby process may be various implemented. Anexample standby process is depicted in FIG. 10, via decisions 1030 and1032. At decision 1030, if a confirming event is not or has not beendetected, a first time condition may be tested, which time condition maybe implemented by comparing a timer to a first time period threshold(TP1). At decision 1032, if a confirming event is not or has not beendetected, a second time condition may be tested, which time conditionmay be implemented by comparing a timer to a second time periodthreshold (TP2). The first and second time conditions may or may notshare either or both the same timer and/or the same time periodthreshold. The first and/or second timer may be started (or re-started),as examples: (i) upon detection of the images retention event; (ii) uponinitiation of image acquisition for the performance test; or (ii) uponsome other event or via some other configuration (e.g., trigger, cue,etc.). The first timer may be started concurrently with one of theforegoing, while the second timer may be started with the same oranother. The time period thresholds TP1 and TP2 may be variouslyconfigured, including responsive to one or more of: the available imagememory, the image acquisition frequency, the image resolution, theanticipated time duration for conducting the performance test, and/orother parameters/conditions. In example embodiments, TP2 is greater thanTP1.

In the example standby process depicted in FIG. 10, at decision 1030, ifthe first timer fails to satisfy (e.g., meet or exceed) the first timeperiod threshold TP1, operations return to the confirming event ofdecision 1026. At decision 1030, if the first timer satisfies TP1,operations flow to decision 1032. At decision 1032, if the second timerfails to satisfy (e.g., meet or exceed) the second time period thresholdTP2, operations flow: to the image discard process, at step 1028 and,from the image discard process, to the acquire images process, at step1022, and then to the images retention event test, at decision 1024. Assuch, if the first timer satisfies TP1 without the second timersatisfying TP2, images may be discarded. Moreover, thepreviously-detected existing images retention event becomes ineffective(i.e., as if that images retention event had not been detected), suchthat the images retention event test is renewed. At decision 1032, ifthe second timer satisfies the second time period threshold TP2,operations end.

In example embodiments, a confirming event may be implemented so as toenable continued acquisition of images in anticipation of imminentathlete initiation of a performance test, while also providing e.g., ifsuch initiation is subject to delay, retention of a reasonable number ofimages (e.g., so as to preserve image storage space for relevantimages). In example embodiments, a confirming event follows an imagesretention event, which images retention event may be detected, aspreviously described, via image processing directed to detecting, e.g.,athlete activity prefatory to performance test conduct. However, afterdetection of an images retention event based, the athlete may or may notinitiate the performance test, whether at all or timely. Accordingly, inexample embodiments, a confirming event may be implemented, such as toenforce a level of discipline as to operations, including as to theathlete.

A confirming event may be variously implemented. In example embodiments,a confirming event may be implemented to be, or to be associated with,as examples: (i) the athlete engaging (or having engaged by anassistant) prescribed input/control capabilities of device(s) 924 (e.g.,pushing a prescribed physical or logical button, or articulating aprescribed voice command as to voice input controls), including via adevice 924 that may be retained by the athlete (e.g., portable device112 of FIG. 1); (ii) the athlete performing (or having performed by anassistant) prescribed act(s), such act(s) being amenable for detectionvia image acquisition or data acquisition capabilities (e.g., exhibitinga prescribed body gesture for reception via the image acquisitioncapabilities, or issuing a prescribed gesture via sensors embedded inapparel, footwear, and/or accessories); (iii) the athlete preparing inthe activity space to conduct a performance test; (iv) the athleteinitiating conduct of a performance test (e.g., a “test start”, asdescribed herein) or otherwise conducting a performance test; and/or (v)a combination of one or more of these.

The descriptions herein respecting image processing to detect an imagesretention event inform image processing for detecting a confirmingevent. In image processing to detect a confirming event, it isunderstood not only that the athlete is present in, and at least attimes moving in, the activity space, but also that the athlete mayimminently initiate, or have initiated, performance test conduct, e.g.,test start. As such, acquired images may be anticipated to includeobject(s) corresponding to the athlete, which object(s) exhibit motionsamong images in imaging sequence. With such understandings, a confirmingevent may be deemed to have occurred if, as an example, motion in theimaging sequence is detected that satisfies (e.g., meets or exceeds) aselected confirming event threshold. In example embodiments, suchconfirming event threshold may be greater than the images retentionevent threshold, which greater value is congruent with detection thatmay include test start, rather than initial position/motionlessness(e.g., greater athlete movement tends to correspond to greater objectmotion in the imaging of that movement).

As to the athlete performing prescribed act(s) as a confirming event,example embodiments may be implemented in which the prescribed act(s)are or are formulated using one or more components. In exampleembodiments, such act(s) may include, e.g.: “test start”; othercomponent(s) implicating athlete movement; “initial position” (aspreviously described); or combinations of one or more of these. Soemploying any such components in formulating such act(s), exampleembodiments may be implemented to detect a confirming event via imageprocessing, including, e.g., image processing informed by thedescriptions as to detecting an images retention event.

If a confirming event is identified via image processing's detection ofa test start, such detection may, in effect, identify a specific imageof the imaging sequence that corresponds to the athlete's initiation ofthe performance test (such specific image sometimes referred to hereinas an “initiation image”). Similarly, such confirming event detectionmay result from means other than image processing (e.g., via dataacquisition, communication and/or processing capabilities, of or amongdevices(s) 924 and/or sensors), which detection may tag a specificimage, such specific image having been acquired at a time correspondingto such detection. Moreover, such confirming event detection may resultfrom a combination of such means with the image processing detection.Such specific image(s) may, in some circumstances, be one of two imagesthat bracket the initiation image (e.g., if the image data indicatesthat the athlete's initiation of the performance test occurred betweentwo consecutive images in the imaging sequence), such that theinitiation image may be resolved via interpolation of two images. Inexample embodiments, such specific image(s) may be treated asplaceholder(s) for further image processing toward concluding on aninitiation image, e.g. further image processing employing more powerfulprocessing methods in order to determine the initiation image.

In some example embodiments, an images retention event test, as indecision 1024, may be omitted in favor of, or may otherwise be combinedin, a confirming event test, as in decision 1026.

From the confirming event test, operations may flow to a terminationevent test, at decision 1034. If a termination event is or has beendetected, operations may flow to the terminate acquired images process,at step 1036. In example embodiments, if a termination event is not orhas not been detected, image acquisition continues and will continueuntil a termination event is detected. In other example embodiments, ifa termination event is not or has not been detected, operations may beimplemented to flow to a standby process (not shown). Any terminationevent standby process may be structured the same as, or similar, to theconfirming event standby process shown at decisions 1030 and 1032. As anexample, a termination event standby process may be implemented based ona max time period threshold (e.g., a time during which the test shouldbe completed, such time period being configured from a priori knowledgeof the performance test and/or from a universe of historical dataassembled from athletes having (properly) conducted such test). In suchexample, the termination event standby process includes a timer that iscompared to the max time period threshold, such that, if no terminationevent is or has been detected when the timer satisfies the threshold,operations flow to the terminate acquired images process, at step 1036.

In example embodiments, a termination event may be implemented so as toenable discontinuation of image acquisition so that unnecessary orirrelevant images are not acquired. In example embodiments, imageacquisition may be terminated following the athlete's completion of thetest.

A termination event may be variously implemented. In exampleembodiments, a termination event may be implemented to be, or to beassociated with, as examples: (i) the athlete engaging (or havingengaged by an assistant) prescribed input/control capabilities ofdevice(s) 1024 (e.g., pushing a prescribed physical or logical button,or articulating a prescribed voice command as to voice input controls),including via a device 1024 that may be retained by the athlete (e.g.,portable device 112 of FIG. 1); (ii) the athlete performing (or havingperformed by an assistant) prescribed act(s), such act(s) being amenablefor detection via image acquisition or data acquisition capabilities(e.g., exhibiting a prescribed body gesture for reception via the imageacquisition capabilities, or issuing a prescribed gesture via sensorsembedded in apparel, footwear, and/or accessories); (iii) the athlete orequipment, or both, reaching or passing prescribed location(s) in or asto the activity space (e.g., relative to one or more test elements), asdetermined via data acquired from sensors embedded in the equipment, inthe athlete's apparel, footwear, and/or accessories, or in a device 1024carried on the athlete, including in combination(s) thereof, and/or incombination(s) with other devices 1024 and/or with other sensors,transceivers or other electronic devices, within the athlete's instantBAN, PAN, or LAN, such location(s) being determined via any of variousmeans, including GPS, AGPS, signaling, signal strength measures, orotherwise; (iv) the athlete completing conduct, or otherwise causingcompletion, of a performance test via, e.g., the athlete's completion ofa component, the athlete's interaction with a test element (e.g.,crossing a finish line) or a test element—acted on by theathlete—achieving a prescribed state change (e.g., an athlete-thrownball transitioning from flight to landing), as described herein (e.g.,such completion sometimes referred to herein by the term “testcompletion”, as previously described); (v) the athlete physicallydeparting the activity space, or remaining in the activity space, butwith no physical activity relevant to the performance test; and/or (vi)a combination of one or more of these.

The descriptions herein respecting image processing to detect an imagesretention event and/or a confirming event inform image processing fordetecting a termination event. In image processing to detect atermination event, it is understood not only (i) that the athlete hasbeen present in, and at least at times has been physically moving in,the activity space, but also (ii) that the athlete will complete conductof the performance test, or that the test will otherwise be completed(e.g., test completion) and, in turn, that the athlete's physicalmovement within the activity space may decline or end (e.g., at least asto the test). As well, the nature of the performance test is known,including any equipment employed (including its size, shape, anticipatedlocation(s)), any relevant interactions between the athlete and theequipment (and the relative timing within the test) and anticipatedstate changes as to the equipment (e.g., including movements thereof,and changes in or termination of such movement(s)). As such, acquiredimages may be anticipated to include object(s) corresponding to theathlete and/or the equipment, at least some of which object(s) willexhibit motion(s) among images, e.g., from image to image in thesequence. With such understandings, a termination event may be deemed tohave occurred, as an example, if objects and objects' motion(s) aredetected which correspond to athlete activity and/or equipment activitythat is consistent with completion of the performance test. Examplesinclude image processing may detect, e.g.: (i) a test completion (e.g.,the athlete having crossed the start-stop line 1008, such as, e.g., anybody part crossing a vertical plane associated with the cone(s)physically demarcating such line 1008, whether such lens is positionedon such line or remote therefrom and/or at an angle thereto; (ii) anathlete activity directed to departure from the activity space, or tomovement into and/or loitering in the periphery of the activity space,including an absence or substantial absence thereof (e.g., any of whichalone or together may indicate that the athlete has ceased orsubstantially ceased movement and/or conduct of the test); (iii) and/or,a (final) state change for equipment (e.g., as anticipated for the testas to known equipment).

If a termination event is identified via image processing's detection ofa test completion, such detection may, in effect, identify a specificimage of the imaging sequence that corresponds to the end point of theperformance test (such specific image sometimes referred to herein as a“completion image”). Similarly, such termination event detection mayresult from means other than image processing (e.g., via dataacquisition, communication and/or processing capabilities, of or amongdevices(s) 924 and/or sensors), which detection may tag a specificimage, such specific image having been acquired at a time correspondingto such detection. Moreover, such termination event detection may resultfrom a combination of such means with the image processing detection.Such specific image(s) may, in some circumstances, be one of two imagesthat bracket the completion image (e.g., if the image data indicatesthat the athlete's completion of the performance test occurred betweentwo consecutive images in the imaging sequence), such that thecompletion image may be resolved via interpolation of two images. Inexample embodiments, such specific image(s) may, as previously statedrespecting an initiation image, be treated as placeholder(s) for furtherimage processing toward concluding on a completion image, e.g. furtherimage processing employing more powerful processing methods in order todetermine the completion image.

Responsive to detection of a termination event at decision 1034 (or to atermination event standby process), operations flow to a terminateacquired images process, at step 1036. In the terminate acquired imagesprocess, image acquisition is terminated. Such termination may bevariously implemented. In example embodiments, such termination may beeffected upon the detection of the termination event. In other exampleembodiments, such termination may be effected after a configured timeperiod has passed from detection of the termination event (e.g., towardrecording additional images relevant or that may be relevant to imageprocessing). Such configured time period may respond to variousunderstandings, estimates or other factors, including, e.g.: timeperiods associated with the performance test; image memory size; imageacquisition frequency; image resolution; number of imagers; safetymargins, etc.).

From termination of image acquisition at step 1036, operations flow todecision 1038, in which a determination is made whether to submit theacquired images to image processing. If the determination at step 1038is not to so submit, operations flow to step 1044, at which stepoperations may be (i) re-started so as to proceed with furtherperformance testing (e.g., to repeat the current performance test forthe test's prescribed number of repetitions, or to advance to the nextperformance test in the battery of tests in which the currentperformance test resides, or to select a new battery of tests or anindividual test), or (ii) ended. If the determination at step 1038 is tosubmit for image processing, operations flow to image processing at step1040, and from imaging processing to a test results/feedback process atstep 1042.

At step 1040, image processing may be performed. In example embodiments,image processing may be implemented as to image data associated withconstituent(s), including various components thereof. In exampleembodiments, as described herein, image processing may be implemented todetect images associated with one or more of test start, testmilestone(s), and/or test completion. As described herein, imageprocessing may yield: an initiation image corresponding to test start; acompletion image corresponding to test completion; and/or a milestoneimage corresponding to each respective test milestone. As describedherein, image processing may yield more than one image corresponding toany one or more of test start, test completion and/or a test milestone.That is, image processing may, in some circumstances, yield two imagesthat bracket the physical event, e.g., if the image data indicates thatthe physical event occurred between two consecutive images in theimaging sequence), in which case, image processing may yield aninterpolated image, i.e., an image that resolves the two images.

In example embodiments, image processing may be performed iteratively.As an example, image processing may be implemented so as to be performedin phases among all objects and the object(s) corresponding to theathlete: (i) in a first phase, image processing may analyze as tomotion(s) corresponding to all or substantially all physical movementcaptured in the imaging (e.g., overall motion present in the image dataamong frames in an image sequence); and (ii) in a second phase, imageprocessing may analyze as to motion(s) corresponding to overall movementof the athlete's body. As another example, image processing may beimplemented so as to be performed in phases among the object(s)corresponding to the athlete: (i) in a first phase, image processing mayanalyze as to motion(s) corresponding to overall movement of theathlete's body and (ii) in a second phase, image processing may analyzeas to motion(s) corresponding to movement or relative movement of/amongthe athlete's head, torso, arms, legs, etc. In either of these foregoingexamples, the objects and motions corresponding to the athlete's body,body parts and body movements may be implemented so that such objectsand motions are analyzed in combination(s), such as aggregate motion orrelative motion, including relative to an object corresponding to testelement(s) (e.g., a club, a ball or a start/stop line). As anotherexample, image processing may be implemented so as to be performed inphases among the object(s) corresponding to the athlete, as well as theobject(s) corresponding to one or more test elements (e.g., a golf cluband a golf ball): (i) in a first phase, image processing may analyze asto motion(s) corresponding to overall movement of the athlete's body andthe equipment, (ii) in a second phase, image processing may analyze asto motion(s) corresponding to movement or relative movement of/among theathlete's head, torso, arms, legs, etc., and relative movement of theone piece of equipment (e.g., a golf club), such as with respect to oneor more of such athlete's body part(s), and (iii) in a third phase,image processing may analyze as to motion(s) corresponding tomovement/change in state as to another piece of equipment (e.g., as tothe golf ball's flight and landing), such as with respect to yet othertest element(s) (e.g., yardage and/or directional indicator(s)). As toeither of these approaches, image processing may be implemented toaddress aberrant motion, such as that associated with physical movementof the device's imaging acquisitions capabilities, particularly thedevice's imaging chip.

In example embodiments, image processing at step 1040 may be implementedso as to be initiated during image acquisition. In such embodiments,such image processing may execute concurrently, or in coordination, withother processes. In such embodiments, for example, image processing maybe employed in earlier steps, such as for the confirming event test atdecision 1026, toward detecting the initiation image thereat, and suchas for the termination event test at decision 1034, toward detecting thecompletion image thereat. As described herein, such confirming eventtest at decision 1026 and such termination event test at decision 1034may identify placeholder images as to an initiation image and/or atermination image, including for further image processing. In such case,such further image processing may be initiated concurrently with orfollowing such tests, with or without any the termination of imageacquisition at step 1036. Moreover, such further image processing mayemploy more powerful processing methods.

Image processing at step 1040 may be implemented to admit input from theathlete. As an example, image processing may be implemented via portableelectronic device(s) 924, including in connection with a mobileapplication. Such device executing such mobile application may provide auser interface experience by which the athlete (or an assistant) engagesthe device's input/control capabilities (e.g., pushing a prescribedphysical or logical button, or articulating a prescribed voice commandas to voice input controls), so as to provide such input. As an example,via such user interface experience, the athlete may be engaged to reviewall or part of an image sequence associated with the athlete'sconstituent conduct, so as to, e.g.: (i) identify irrelevant portions ofthe imaging, e.g., prefatory and/or post-completion activities, (ii)associate one or more candidate images with one or more of test start,test completion, and/or test milestone(s) (e.g., the athlete selects aframe which the athlete considers to display an image corresponding tothe athlete's initiation or completion of the performance test or of anytest milestone thereof, and/or (iii) identify object(s) in the image(e.g., via a touch-sensitive display, the athlete may select orcircumscribe a piece of equipment and/or the athlete's body or selectedbody parts, any one or more of which identifications may enhance imageprocessing founded on such object(s)). Toward so engaging the athlete,the user interface experience may display queries, requests,instructions, guidance or other feedforward so as to directproper/timely input from the athlete.

In example embodiments, image processing at step 1040 may yield outputsthat are provided to the test results/feedback process, at step 1042.Such outputs may include any one or more of the initiation, completionand milestone images (e.g., for display to the athlete or others). Suchoutputs may also include data that enables measurements, including informat and content, appropriate to measurements provided via the testresults/feedback process, at step 1042. As an example, such output datamay include the frame numbers, frame times, or other frame addressing,any of which may be absolute or against a reference. Such output datamay also be provided together with the image acquisition frequency, anytime offsets (e.g., shutter offset among plural imagers), or the like.Such output data, via format and content, enables, e.g., the measure oftime differences, which time differences may be test results or mayenable calculation of test results. As an example, for the arrowheadagility exercise, the image processing output may include the initiationimage, the completion image and the image acquisition frequency inframes per second, with the initiation image denoted as frame #F1, thecompletion image denoted by frame #F2 and the image acquisitionfrequency denoted as FPS, such that measurement of the elapsed time forthe test is the (#F2-#F1)/FPS. In such case, if #FP1=0, #FP2=3000, andFPS=50 fps, the measurement is (3000-0)/50=60 seconds. As anotherexample, for the power ball chest launch exercise, similar outputs maybe provided, with the measurement yielding an elapsed time capturing theball's flight, which elapsed time, together with the balls known weightand the athlete's known profile (height, etc.), may be applied to apredetermined ballistics formula toward measuring distance of the ball'sflight.

In certain further descriptive embodiments, aspects of this disclosureinvolve obtaining, storing, and/or processing athletic data relating tothe physical movements of an athlete. The movements may be part of oneor more activities. An activity, as such term may be used herein, mayinclude, as an example, golf. A constituent, as such term is usedherein, may include, as an example, a swing of a golf driver (hereafter,sometimes referred to as a “swing”). Components of a golf driver swingare known and some of which are described herein. In other exampleactivities, a constituent may also be a swing, but of other, relevantequipment. A constituent is a movement that may include one or morecomponents. A constituent, and each component, has physicalcharacteristics, including, e.g., various velocities, accelerations,rotations, durations, etc. In example embodiments, a constituent (whichmay be equivalent to a feature disclosed above), e.g. a swing, may becaptured in image data (e.g., images in sequence or video) via one ormore image acquisition devices (hereafter, each such device may bereferred to as a “camera”). A camera may be provided in a smart phone,such as an HTC One X+. In capturing the swing, the image data capturesmovement of the user's body and body parts, as well as equipment, suchas a golf club. The body, body parts and equipment may be captured inthe image data as objects. The movements of the swing (and/or anyobjects in the image data) are captured in the image data as motion.Components of the swing are captured in the image data as swingfeatures. For example, at any given time, more than one component mayoccur (e.g., body part movement and club movement), such that more thanone swing feature may occur.

Imaging of the activity, movement or its constituents, such as of aswing, its components, and the velocities, accelerations, rotationsthereof may be referenced with respect to one or more selected axes(e.g., in the image, a coordinate system and/or axes of rotations may beprovided) and/or reference point(s). Imaging may also be variouslytimed, including absolute (chronography) or relative to the shutter ofan image-capturing device (e.g., fps).

Using a golf swing as one example, not all components, features, etc.may be relevant for the purposes of various embodiments. A component'srelevance may be responsive to, among other things, a relationship toswing results (e.g., changes in the component may have large, medium orsmall impact on the distance or accuracy for a golf ball's flight); thecomplexity of its movement (including as to velocities, accelerations,rotations and any other of its characteristics); and/or challengesassociated with imaging or analysis of such component/feature. Theimaging and imaging analysis challenges may be related to, e.g.: theavailable computing power (e.g., local, distributed, and time based);resource (energy) consumption issues; imaging issues (e.g., resolution,fps, etc.). A component may be relevant because such component ispresent in plural swings, e.g., in the various swings associated withthe golf clubs found in a typical user's bag, and/or among swings ofdifferent sports. As such, image data associated with irrelevantcomponents may not be analyzed. Moreover, swing features may or may notbe contiguous in the image data sequence. As to any selected swingfeature in the image data sequence, the may be: simultaneous with one ormore other swing features (i.e., appear in the exact same images orvideo frames); overlapping with others (i.e., appear in some but not allimages or video frames); contiguous with others (i.e., the selectedfeature's last frame is the frame just before the other feature's firstframe); or isolated from all other features. All swing features,together, may include all relevant image data associated with thecaptured swing imaging.

One or more components of a constituent may not be relevant in effectingvarious embodiments, or may not be relevant throughout. As such, thesecomponents may either (i) not ever part of the analysis or (ii) notalways part of the analysis (e.g., the component may be relevant in somecases, such as, being a back-up data source if another component cannotbe imaged). Relevance may be based on the complexity and/or resourcedemands of that component's analysis. Relevance may be determined basedon diminishing returns from its analysis. Relevance may be based onother factors, or combinations of any of these. As to diminishingreturns in a golf swing, for example, the user's trunk rotation (angularvelocity and/or range) may be relatively important at one time (thus,analyzed in the image domain, including perhaps to the exclusion of oneor more other components), and may be relatively unimportant at anothertime (thus, perhaps excluded from the analysis that now focuses on oneor more other components, including, e.g., one or more of thepreviously-excluded components).

Analysis may be of the image data overall, swing feature-by-swingfeature, or as a sequence of swing feature data. As per above, imagedata may be analyzed in combination with or otherwise responsive toother data, such as sensor data and/or swing result data. Analysisoutputs are input, alone or together with other input (e.g., other inputmay be results data, user input or otherwise), to a feedback generatorfunction. The feedback generator function may be provided as part of oneor more computer-implemented instructions on a non-transitorycomputer-readable medium, including those described herein, and/or maybe provided as a service (e.g., a web-service, or otherwise), or somecombination. The feedback generator generates feedback signal(s), whichfeedback signals are provided to the user. The feedback signal(s) may bevariously so provided, including, as examples, through additionalhardware and/or software functions, or one or more transducers, or acombination. Examples, include using the HTC One X+'s native functions,e.g., the HTC One X+'s speakers and/or camera LEDs.

We claim:
 1. A computer-implemented method for providing audiblefeedback to an athlete during performance of a physical activitycomprising: receiving at a computer in real-time, a plurality ofsequential images during a first athlete's performance of an physicalactivity; processing by the computer in real-time using an optical flowprocess, pixels from the plurality of sequential images to identifyimage data of the first athlete performing a first feature of a firstathletic movement involving a sporting device during the physicalactivity; in response to identifying the performance of the firstfeature, outputting a real-time first audio feedback signal having afirst audible tone having a first ADSR envelope based upon the movementproperties of the sporting device during the first feature; detecting,as part of the real-time processing of pixels from the plurality ofsequential images, image data within the plurality of images indicativethat the first athlete is performing a second feature of the firstathletic movement; outputting, in real-time, a second audio feedbacksignal having a second tone having a second ADSR envelope based upon themovement properties of the sporting device during the second featuresuch that the athlete receives audio feedback during performance of theathletic movement configured to provide audible tempo feedback inregards to the athlete's performance of the first and second features ofthe athletic activity, where the audible tempo feedback is based onprior recorded movement properties of the sporting device associatedwith the first athlete; and, calculating an athletic score based on theathlete's performance of the first and second features of the athleticactivity.
 2. The method of claim 1, wherein the first audio feedbacksignal is a first audible tone at a first frequency and generating thesecond audio feedback signal comprises modulating the audible tone to asecond frequency.
 3. The method of claim 1, wherein the identificationof the first feature comprises identifying an initiation imagecomprising: identifying pixels that correspond to at least one of aspecific first body portion or sporting device, wherein the first bodyportion or sporting device is selected based upon a predeterminedphysical activity the athlete is to perform; and determining, based uponthe identified pixels, whether the pixel data is altered between aplurality of images within the sequential images such that thealteration satisfies a first threshold.
 4. The method of claim 1,wherein an output of the optical flow process is provided as an input toa motion entropy determination process comprising: providing flow fielddata comprising a pixel-distance change of an identified object from afirst image to a second image; and using the flow field data to identifya specific type of motion of the athlete represented in the image dataduring performance of the physical activity.
 5. The method of claim 4,wherein the second feature is detected from a motion parameter based onat least one of a velocity value, an acceleration value, a location of abody portion of the athlete, or a location of a sporting device withinthe image data.
 6. The method of claim 5, wherein the motion parameteris determined based upon, at least in part, determining that a velocityvalue or an acceleration value meets a first threshold.
 7. The method ofclaim 5, further comprising: utilizing the motion parameter in thegeneration of the second audio feedback signal.
 8. The method of claim4, wherein the physical activity is a golf swing having an upswingathletic movement and a subsequent downswing athletic movement; andwherein detecting the image data that the first athlete is performingthe first feature comprises detecting pixel data indicative that a golfclub is within a first distance from a ground surface and detecting theimage data that the second athlete is performing the second feature ofthe upswing athletic movement is detected from pixel data indicativethat the golf club is within a second distance from a ground surface. 9.The method of claim 2, further comprising: based upon the detection ofat least one of the first and the second feature, transmitting a thirdaudible feedback signal having a third audible tone having a third ADSRenvelope at a predetermined time based upon the occurrence of the firstor second feature configured to indicate the proper timing for theathlete to perform an additional feature of the athletic performance.10. A computer-implemented method for determining an athletic attributeof an athlete comprising: receiving a plurality of sequential images,wherein at least a first image comprises image data of an athlete beforeinitiating performance of a predetermined physical activity and aplurality of subsequent images comprise image data of the athleteperforming the predetermined physical activity; processing using anoptical flow process at least a portion of the plurality of subsequentimages to identify a first range of images located after the firstimage, wherein the identification is based upon pixel data for athreshold quantity of pixels in the subsequent images reaching a firstthreshold level indicative that movement of an object in the images hasoccurred; processing the image data to locate an object having a knowndimension, and using the known dimension to calibrate the image data;processing images within the first range of images to identify aninitiation image of a first feature involving a sporting device of thephysical activity, comprising: identifying pixels in the first range ofimages that correspond to a specific first body portion of the athlete,wherein the first body portion is selected based upon the predeterminedphysical activity; determining, based upon the identified pixels,whether the pixel data is altered such that alteration satisfies a firstbody portion movement quality threshold; and utilizing the initiationimage and the determination of the first body portion movement qualitythreshold in a determination that the athlete performed the firstfeature; in response to identifying the performance of the firstfeature, transmitting a real-time first audio feedback signal having afirst audible tone having a first ADSR envelope based upon movementproperties of the sporting device during the first feature, where thefirst audible tone is configured to provide audible tempo feedback forthe athlete's performance of the first feature based on prior recordedmovement properties of the sporting device or the first athlete; andcalculate an athletic score based on the movement properties of thesporting device during the first feature.
 11. The method of claim 10,further comprising: processing at least a portion of the plurality ofsequential images to locate a completion image sequentially locatedafter the first image, the completion image comprising image data of theathlete immediately upon completing the first feature of thepredetermined physical activity.
 12. The method of claim 11, furthercomprising: calculating a physical activity duration based upon thelocated initiation image and the located end image.
 13. The method ofclaim 12, wherein the output of the optical flow process is provided asan input to a motion entropy determination process comprising: providingflow field data comprising a pixel-distance change of an identifiedobject from a first image to a second image; and using the flow fielddata to identify a specific type of motion of the athlete represented inthe image data during performance of the predetermined physicalactivity.
 14. The method of claim 10, further comprising: detecting, aspart of the real-time processing, image data within the plurality ofimages indicative that the first athlete is performing a second featureof a first athletic movement; and outputting, in real-time, a secondaudio feedback signal having a second audible tone having a second ADSRenvelope based upon the movement properties of the second feature suchthat the athlete receives audio feedback during performance of theathletic movement configured to provide audible tempo feedback inregards to the athlete's performance of the first and second features ofthe athletic activity.
 15. The method of claim 14, wherein the firstaudio feedback signal is a first audible tone at a first frequency andgenerating the second audio feedback signal comprises modulating theaudible tone to a second frequency.
 16. The method of claim 10, whereinthe identification of the first feature comprises identifying aninitiation image comprising: identifying pixels that correspond to atleast one of a specific first body portion or sporting device, whereinthe first body portion or sporting device is selected based upon apredetermined physical activity the athlete is to perform; anddetermining, based upon the identified pixels, whether the pixel data isaltered between a plurality of images within the sequential images suchthat the alteration satisfies a first threshold.
 17. The method of claim14, wherein the second feature is detected from a motion parameter basedon at least one of a velocity value, an acceleration value, a locationof a body portion of the athlete, or a location of a sporting devicewithin the image data.
 18. The method of claim 17, wherein the motionparameter is determined based upon, at least in part, determining that avelocity value or an acceleration value meets a first threshold.